Overview

Brought to you by YData

Dataset statistics

Number of variables129
Number of observations26208
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.0 MiB
Average record size in memory1.1 KiB

Variable types

DateTime1
Categorical128

Dataset

DescriptionSix-Month Monitoring Dataset from a 10-Turbine Onshore Wind Farm in Greece.
URLhttps://doi.org/10.5281/zenodo.14546479

Alerts

Gear Oil Temp. Avg. [°C] has constant value "0" Constant
Gear Bearing Temp. Avg. [°C] has constant value "0" Constant
Gear Oil TemperatureLevel2_3 Avg. [°C] has constant value "0" Constant
Ambient WindSpeed Estimated Avg. [m/s] has constant value "0" Constant
Grid Production PossibleInductive Avg. [var] has constant value "0" Constant
Grid Production PossibleInductive Max. [var] has constant value "0" Constant
Grid Production PossibleInductive Min. [var] has constant value "0" Constant
Grid Production PossibleInductive StdDev [var] has constant value "0" Constant
Grid Production PossibleCapacitive Avg. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Max. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Min. [var] has constant value "0" Constant
Grid Production PossibleCapacitive StdDev [var] has constant value "0" Constant
Reactive power set point [var] has constant value "0" Constant
Spinner Temp. SlipRing Avg. [°C] has constant value "0" Constant
HourCounters Average Total Avg. [h] has constant value "0" Constant
Total hour counter [h] has constant value "0" Constant
Grid on hours [h] has constant value "0" Constant
Grid ok hours [h] has constant value "0" Constant
Turbine ok hours [h] has constant value "0" Constant
Run hours [h] has constant value "0" Constant
Generator 1 hours [h] has constant value "0" Constant
Generator 2 hours [h] has constant value "0" Constant
Yaw hours [h] has constant value "0" Constant
Service hours [h] has constant value "0" Constant
Ambient ok hours [h] has constant value "0" Constant
Wind ok hours [h] has constant value "0" Constant
Active power generator 0, Total accumulated [W] has constant value "0" Constant
Active power generator 1, Total accumulated [W] has constant value "0" Constant
Reactive power generator 1, Total accumulated [var] has constant value "0" Constant
Reactive power generator 2, Total accumulated [var] has constant value "0" Constant
Active power limit [W] is highly overall correlated with HourCounters Average GridOn Avg. [h]High correlation
Active power limit source is highly overall correlated with HourCounters Average GridOn Avg. [h] and 2 other fieldsHigh correlation
Blades PitchAngle Min. [°] is highly overall correlated with Blades PitchAngle StdDev [°] and 2 other fieldsHigh correlation
Blades PitchAngle StdDev [°] is highly overall correlated with Blades PitchAngle Min. [°]High correlation
Generator RPM Avg. [RPM] is highly overall correlated with Rotor RPM Avg. [RPM]High correlation
Generator RPM Max. [RPM] is highly overall correlated with Rotor RPM Max. [RPM]High correlation
Generator RPM Min. [RPM] is highly overall correlated with Rotor RPM Min. [RPM]High correlation
Generator RPM StdDev [RPM] is highly overall correlated with Rotor RPM StdDev [RPM]High correlation
Grid Production CosPhi Avg. is highly overall correlated with Production LatestAverage Active Power Gen 0 Avg. [W] and 1 other fieldsHigh correlation
Grid Production CurrentPhase1 Avg. [A] is highly overall correlated with Grid Production CurrentPhase2 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase2 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase3 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Max. [W] is highly overall correlated with Grid Production Power Max. [W]High correlation
Grid Production PossiblePower Min. [W] is highly overall correlated with Grid Production Power Min. [W]High correlation
Grid Production PossiblePower StdDev [W] is highly overall correlated with Grid Production Power StdDev [W]High correlation
Grid Production Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production Power Max. [W] is highly overall correlated with Grid Production PossiblePower Max. [W]High correlation
Grid Production Power Min. [W] is highly overall correlated with Grid Production PossiblePower Min. [W]High correlation
Grid Production Power StdDev [W] is highly overall correlated with Grid Production PossiblePower StdDev [W]High correlation
Grid Production ReactivePower Avg. [W] is highly overall correlated with Blades PitchAngle Min. [°] and 6 other fieldsHigh correlation
Grid Production ReactivePower Max. [W] is highly overall correlated with Grid Production ReactivePower Avg. [W]High correlation
Grid Production VoltagePhase1 Avg. [V] is highly overall correlated with Grid Production VoltagePhase2 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase2 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase3 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
HourCounters Average AlarmActive Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average AmbientOk Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average Gen1 Avg. [h] is highly overall correlated with HourCounters Average Gen2 Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average Gen2 Avg. [h] is highly overall correlated with Blades PitchAngle Min. [°] and 6 other fieldsHigh correlation
HourCounters Average GridOk Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average GridOn Avg. [h] is highly overall correlated with Active power limit [W] and 4 other fieldsHigh correlation
HourCounters Average Run Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average ServiceOn Avg. [h] is highly overall correlated with HourCounters Average GridOk Avg. [h]High correlation
HourCounters Average TurbineOk Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 1 other fieldsHigh correlation
Power factor set point is highly overall correlated with Active power limit source and 2 other fieldsHigh correlation
Power factor set point source is highly overall correlated with Active power limit source and 2 other fieldsHigh correlation
Production LatestAverage Active Power Gen 0 Avg. [W] is highly overall correlated with Grid Production CosPhi Avg. and 3 other fieldsHigh correlation
Production LatestAverage Active Power Gen 1 Avg. [W] is highly overall correlated with HourCounters Average Gen1 Avg. [h]High correlation
Production LatestAverage Active Power Gen 2 Avg. [W] is highly overall correlated with HourCounters Average Gen2 Avg. [h]High correlation
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly overall correlated with Grid Production CosPhi Avg. and 4 other fieldsHigh correlation
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly overall correlated with Production LatestAverage Total Reactive Power Avg. [var]High correlation
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 1 other fieldsHigh correlation
Production LatestAverage Total Active Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Production LatestAverage Total Reactive Power Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 2 other fieldsHigh correlation
Rotor RPM Avg. [RPM] is highly overall correlated with Generator RPM Avg. [RPM]High correlation
Rotor RPM Max. [RPM] is highly overall correlated with Generator RPM Max. [RPM]High correlation
Rotor RPM Min. [RPM] is highly overall correlated with Generator RPM Min. [RPM]High correlation
Rotor RPM StdDev [RPM] is highly overall correlated with Generator RPM StdDev [RPM]High correlation
Generator RPM Max. [RPM] is highly imbalanced (62.8%) Imbalance
Generator RPM Min. [RPM] is highly imbalanced (56.8%) Imbalance
Generator RPM Avg. [RPM] is highly imbalanced (56.5%) Imbalance
Generator RPM StdDev [RPM] is highly imbalanced (57.2%) Imbalance
Generator Bearing Temp. Avg. [°C] is highly imbalanced (72.9%) Imbalance
Generator Phase1 Temp. Avg. [°C] is highly imbalanced (73.8%) Imbalance
Generator Phase2 Temp. Avg. [°C] is highly imbalanced (76.4%) Imbalance
Generator Phase3 Temp. Avg. [°C] is highly imbalanced (76.5%) Imbalance
Generator SlipRing Temp. Avg. [°C] is highly imbalanced (55.9%) Imbalance
Generator Bearing2 Temp. Avg. [°C] is highly imbalanced (77.1%) Imbalance
Hydraulic Oil Temp. Avg. [°C] is highly imbalanced (64.3%) Imbalance
Gear Oil TemperatureBasis Avg. [°C] is highly imbalanced (61.9%) Imbalance
Gear Oil TemperatureLevel1 Avg. [°C] is highly imbalanced (64.0%) Imbalance
Gear Bearing TemperatureHSRotorEnd Avg. [°C] is highly imbalanced (74.4%) Imbalance
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C] is highly imbalanced (67.6%) Imbalance
Gear Bearing TemperatureHSMiddle Avg. [°C] is highly imbalanced (68.1%) Imbalance
Gear Bearing TemperatureHollowShaftRotor Avg. [°C] is highly imbalanced (57.5%) Imbalance
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C] is highly imbalanced (65.3%) Imbalance
Nacelle Temp. Avg. [°C] is highly imbalanced (54.6%) Imbalance
Rotor RPM Max. [RPM] is highly imbalanced (54.6%) Imbalance
Rotor RPM Avg. [RPM] is highly imbalanced (58.6%) Imbalance
Ambient WindSpeed Max. [m/s] is highly imbalanced (89.5%) Imbalance
Ambient WindSpeed Min. [m/s] is highly imbalanced (86.0%) Imbalance
Ambient WindSpeed Avg. [m/s] is highly imbalanced (91.2%) Imbalance
Ambient WindSpeed StdDev [m/s] is highly imbalanced (70.1%) Imbalance
Ambient WindDir Relative Avg. [°] is highly imbalanced (82.6%) Imbalance
Ambient WindDir Absolute Avg. [°] is highly imbalanced (84.1%) Imbalance
Grid InverterPhase1 Temp. Avg. [°C] is highly imbalanced (69.0%) Imbalance
Grid RotorInvPhase1 Temp. Avg. [°C] is highly imbalanced (60.6%) Imbalance
Grid RotorInvPhase2 Temp. Avg. [°C] is highly imbalanced (54.6%) Imbalance
Grid RotorInvPhase3 Temp. Avg. [°C] is highly imbalanced (57.3%) Imbalance
Grid Production Power Avg. [W] is highly imbalanced (80.1%) Imbalance
Grid Production CosPhi Avg. is highly imbalanced (73.4%) Imbalance
Grid Production Frequency Avg. [Hz] is highly imbalanced (95.1%) Imbalance
Grid Production VoltagePhase1 Avg. [V] is highly imbalanced (92.4%) Imbalance
Grid Production VoltagePhase2 Avg. [V] is highly imbalanced (91.6%) Imbalance
Grid Production VoltagePhase3 Avg. [V] is highly imbalanced (91.7%) Imbalance
Grid Production CurrentPhase1 Avg. [A] is highly imbalanced (79.1%) Imbalance
Grid Production CurrentPhase2 Avg. [A] is highly imbalanced (78.7%) Imbalance
Grid Production CurrentPhase3 Avg. [A] is highly imbalanced (79.7%) Imbalance
Grid Production Power Max. [W] is highly imbalanced (73.4%) Imbalance
Grid Production Power Min. [W] is highly imbalanced (74.7%) Imbalance
Grid Busbar Temp. Avg. [°C] is highly imbalanced (65.7%) Imbalance
Grid Production Power StdDev [W] is highly imbalanced (73.6%) Imbalance
Grid Production ReactivePower Avg. [W] is highly imbalanced (62.3%) Imbalance
Grid Production PossiblePower Avg. [W] is highly imbalanced (81.5%) Imbalance
Grid Production PossiblePower Max. [W] is highly imbalanced (77.7%) Imbalance
Grid Production PossiblePower Min. [W] is highly imbalanced (77.2%) Imbalance
Grid Production PossiblePower StdDev [W] is highly imbalanced (79.4%) Imbalance
Active power limit [W] is highly imbalanced (98.3%) Imbalance
Active power limit source is highly imbalanced (99.6%) Imbalance
Power factor set point is highly imbalanced (99.6%) Imbalance
Power factor set point source is highly imbalanced (99.6%) Imbalance
Controller Ground Temp. Avg. [°C] is highly imbalanced (90.3%) Imbalance
Controller Top Temp. Avg. [°C] is highly imbalanced (72.2%) Imbalance
Controller Hub Temp. Avg. [°C] is highly imbalanced (77.6%) Imbalance
Controller VCP Temp. Avg. [°C] is highly imbalanced (59.6%) Imbalance
Controller VCP ChokecoilTemp. Avg. [°C] is highly imbalanced (79.1%) Imbalance
Spinner Temp. Avg. [°C] is highly imbalanced (52.4%) Imbalance
Blades PitchAngle Min. [°] is highly imbalanced (58.8%) Imbalance
Blades PitchAngle Max. [°] is highly imbalanced (58.3%) Imbalance
Blades PitchAngle Avg. [°] is highly imbalanced (59.8%) Imbalance
HVTrafo Phase1 Temp. Avg. [°C] is highly imbalanced (81.6%) Imbalance
HVTrafo Phase2 Temp. Avg. [°C] is highly imbalanced (81.0%) Imbalance
HVTrafo Phase3 Temp. Avg. [°C] is highly imbalanced (79.8%) Imbalance
HVTrafo AirOutlet Temp. Avg. [°C] is highly imbalanced (56.4%) Imbalance
HourCounters Average GridOn Avg. [h] is highly imbalanced (98.8%) Imbalance
HourCounters Average GridOk Avg. [h] is highly imbalanced (98.6%) Imbalance
HourCounters Average TurbineOk Avg. [h] is highly imbalanced (98.3%) Imbalance
HourCounters Average Run Avg. [h] is highly imbalanced (96.3%) Imbalance
HourCounters Average Gen1 Avg. [h] is highly imbalanced (81.6%) Imbalance
HourCounters Average Gen2 Avg. [h] is highly imbalanced (66.1%) Imbalance
HourCounters Average ServiceOn Avg. [h] is highly imbalanced (99.0%) Imbalance
HourCounters Average AmbientOk Avg. [h] is highly imbalanced (97.2%) Imbalance
HourCounters Average WindOk Avg. [h] is highly imbalanced (68.6%) Imbalance
HourCounters Average AlarmActive Avg. [h] is highly imbalanced (95.7%) Imbalance
Production LatestAverage Active Power Gen 0 Avg. [W] is highly imbalanced (74.3%) Imbalance
Production LatestAverage Active Power Gen 1 Avg. [W] is highly imbalanced (83.0%) Imbalance
Production LatestAverage Active Power Gen 2 Avg. [W] is highly imbalanced (77.0%) Imbalance
Production LatestAverage Total Active Power Avg. [W] is highly imbalanced (80.2%) Imbalance
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly imbalanced (72.8%) Imbalance
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly imbalanced (58.2%) Imbalance
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly imbalanced (63.2%) Imbalance
Active power generator 2, Total accumulated [W] is highly imbalanced (99.6%) Imbalance
Total Active power [W] is highly imbalanced (97.6%) Imbalance
Reactive power generator 0,Total accumulated [var] is highly imbalanced (95.8%) Imbalance
Total reactive power [var] is highly imbalanced (95.8%) Imbalance
Timestamp has unique values Unique

Reproduction

Analysis started2025-05-15 12:25:01.001219
Analysis finished2025-05-15 12:25:30.995177
Duration29.99 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Timestamp
Date

Unique 

Distinct26208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Minimum2020-01-01 00:00:00
Maximum2020-06-30 23:50:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-15T14:25:31.035941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-15T14:25:31.119125image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Generator RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24329 
1
 
1879

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24329
92.8%
1 1879
 
7.2%

Length

2025-05-15T14:25:31.193023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:31.229041image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24329
92.8%
1 1879
 
7.2%

Most occurring characters

ValueCountFrequency (%)
0 24329
92.8%
1 1879
 
7.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24329
92.8%
1 1879
 
7.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24329
92.8%
1 1879
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24329
92.8%
1 1879
 
7.2%

Generator RPM Min. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23888 
1
 
2320

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23888
91.1%
1 2320
 
8.9%

Length

2025-05-15T14:25:31.423033image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:31.459316image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23888
91.1%
1 2320
 
8.9%

Most occurring characters

ValueCountFrequency (%)
0 23888
91.1%
1 2320
 
8.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23888
91.1%
1 2320
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23888
91.1%
1 2320
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23888
91.1%
1 2320
 
8.9%

Generator RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23863 
1
 
2345

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23863
91.1%
1 2345
 
8.9%

Length

2025-05-15T14:25:31.503075image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:31.540509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23863
91.1%
1 2345
 
8.9%

Most occurring characters

ValueCountFrequency (%)
0 23863
91.1%
1 2345
 
8.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23863
91.1%
1 2345
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23863
91.1%
1 2345
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23863
91.1%
1 2345
 
8.9%

Generator RPM StdDev [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23916 
1
 
2292

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23916
91.3%
1 2292
 
8.7%

Length

2025-05-15T14:25:31.585048image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:31.621384image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23916
91.3%
1 2292
 
8.7%

Most occurring characters

ValueCountFrequency (%)
0 23916
91.3%
1 2292
 
8.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23916
91.3%
1 2292
 
8.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23916
91.3%
1 2292
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23916
91.3%
1 2292
 
8.7%

Generator Bearing Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24993 
1
 
1215

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24993
95.4%
1 1215
 
4.6%

Length

2025-05-15T14:25:31.667199image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:31.702980image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24993
95.4%
1 1215
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 24993
95.4%
1 1215
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24993
95.4%
1 1215
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24993
95.4%
1 1215
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24993
95.4%
1 1215
 
4.6%

Generator Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25044 
1
 
1164

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Length

2025-05-15T14:25:31.747494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:31.783484image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Generator Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25197 
1
 
1011

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Length

2025-05-15T14:25:31.825897image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:31.863312image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Most occurring characters

ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Generator Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25199 
1
 
1009

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25199
96.2%
1 1009
 
3.8%

Length

2025-05-15T14:25:31.905893image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:31.941635image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25199
96.2%
1 1009
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25199
96.2%
1 1009
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25199
96.2%
1 1009
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25199
96.2%
1 1009
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25199
96.2%
1 1009
 
3.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23813 
1
2395 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23813
90.9%
1 2395
 
9.1%

Length

2025-05-15T14:25:31.985714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:32.022302image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23813
90.9%
1 2395
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 23813
90.9%
1 2395
 
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23813
90.9%
1 2395
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23813
90.9%
1 2395
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23813
90.9%
1 2395
 
9.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25236 
1
 
972

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25236
96.3%
1 972
 
3.7%

Length

2025-05-15T14:25:32.067025image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:32.104560image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25236
96.3%
1 972
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25236
96.3%
1 972
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25236
96.3%
1 972
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25236
96.3%
1 972
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25236
96.3%
1 972
 
3.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
21846 
1
4362 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21846
83.4%
1 4362
 
16.6%

Length

2025-05-15T14:25:32.147997image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:32.184992image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 21846
83.4%
1 4362
 
16.6%

Most occurring characters

ValueCountFrequency (%)
0 21846
83.4%
1 4362
 
16.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 21846
83.4%
1 4362
 
16.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 21846
83.4%
1 4362
 
16.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 21846
83.4%
1 4362
 
16.6%

Hydraulic Oil Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24435 
1
 
1773

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24435
93.2%
1 1773
 
6.8%

Length

2025-05-15T14:25:32.231433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:32.268039image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24435
93.2%
1 1773
 
6.8%

Most occurring characters

ValueCountFrequency (%)
0 24435
93.2%
1 1773
 
6.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24435
93.2%
1 1773
 
6.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24435
93.2%
1 1773
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24435
93.2%
1 1773
 
6.8%

Gear Oil Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:32.310856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:32.347037image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Gear Bearing Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:32.386920image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:32.420279image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24263 
1
 
1945

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24263
92.6%
1 1945
 
7.4%

Length

2025-05-15T14:25:32.461462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:32.497427image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24263
92.6%
1 1945
 
7.4%

Most occurring characters

ValueCountFrequency (%)
0 24263
92.6%
1 1945
 
7.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24263
92.6%
1 1945
 
7.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24263
92.6%
1 1945
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24263
92.6%
1 1945
 
7.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24417 
1
 
1791

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24417
93.2%
1 1791
 
6.8%

Length

2025-05-15T14:25:32.539948image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:32.577657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24417
93.2%
1 1791
 
6.8%

Most occurring characters

ValueCountFrequency (%)
0 24417
93.2%
1 1791
 
6.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24417
93.2%
1 1791
 
6.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24417
93.2%
1 1791
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24417
93.2%
1 1791
 
6.8%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:32.620023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:32.653398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25078 
1
 
1130

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25078
95.7%
1 1130
 
4.3%

Length

2025-05-15T14:25:32.694596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:32.730832image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25078
95.7%
1 1130
 
4.3%

Most occurring characters

ValueCountFrequency (%)
0 25078
95.7%
1 1130
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25078
95.7%
1 1130
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25078
95.7%
1 1130
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25078
95.7%
1 1130
 
4.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24657 
1
 
1551

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24657
94.1%
1 1551
 
5.9%

Length

2025-05-15T14:25:32.773156image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:32.810901image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24657
94.1%
1 1551
 
5.9%

Most occurring characters

ValueCountFrequency (%)
0 24657
94.1%
1 1551
 
5.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24657
94.1%
1 1551
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24657
94.1%
1 1551
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24657
94.1%
1 1551
 
5.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24692 
1
 
1516

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24692
94.2%
1 1516
 
5.8%

Length

2025-05-15T14:25:32.853791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:32.889686image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24692
94.2%
1 1516
 
5.8%

Most occurring characters

ValueCountFrequency (%)
0 24692
94.2%
1 1516
 
5.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24692
94.2%
1 1516
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24692
94.2%
1 1516
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24692
94.2%
1 1516
 
5.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23941 
1
 
2267

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23941
91.3%
1 2267
 
8.7%

Length

2025-05-15T14:25:32.934385image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:32.971702image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23941
91.3%
1 2267
 
8.7%

Most occurring characters

ValueCountFrequency (%)
0 23941
91.3%
1 2267
 
8.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23941
91.3%
1 2267
 
8.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23941
91.3%
1 2267
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23941
91.3%
1 2267
 
8.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24504 
1
 
1704

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24504
93.5%
1 1704
 
6.5%

Length

2025-05-15T14:25:33.016570image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:33.054402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24504
93.5%
1 1704
 
6.5%

Most occurring characters

ValueCountFrequency (%)
0 24504
93.5%
1 1704
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24504
93.5%
1 1704
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24504
93.5%
1 1704
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24504
93.5%
1 1704
 
6.5%

Nacelle Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23706 
1
2502 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Length

2025-05-15T14:25:33.097619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:33.134494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Most occurring characters

ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Rotor RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23710 
1
2498 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23710
90.5%
1 2498
 
9.5%

Length

2025-05-15T14:25:33.180950image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:33.217659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23710
90.5%
1 2498
 
9.5%

Most occurring characters

ValueCountFrequency (%)
0 23710
90.5%
1 2498
 
9.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23710
90.5%
1 2498
 
9.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23710
90.5%
1 2498
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23710
90.5%
1 2498
 
9.5%

Rotor RPM Min. [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23185 
1
3023 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23185
88.5%
1 3023
 
11.5%

Length

2025-05-15T14:25:33.262444image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:33.301967image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23185
88.5%
1 3023
 
11.5%

Most occurring characters

ValueCountFrequency (%)
0 23185
88.5%
1 3023
 
11.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23185
88.5%
1 3023
 
11.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23185
88.5%
1 3023
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23185
88.5%
1 3023
 
11.5%

Rotor RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24026 
1
 
2182

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24026
91.7%
1 2182
 
8.3%

Length

2025-05-15T14:25:33.346895image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:33.383820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24026
91.7%
1 2182
 
8.3%

Most occurring characters

ValueCountFrequency (%)
0 24026
91.7%
1 2182
 
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24026
91.7%
1 2182
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24026
91.7%
1 2182
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24026
91.7%
1 2182
 
8.3%

Rotor RPM StdDev [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23198 
1
3010 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23198
88.5%
1 3010
 
11.5%

Length

2025-05-15T14:25:33.430151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:33.466796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23198
88.5%
1 3010
 
11.5%

Most occurring characters

ValueCountFrequency (%)
0 23198
88.5%
1 3010
 
11.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23198
88.5%
1 3010
 
11.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23198
88.5%
1 3010
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23198
88.5%
1 3010
 
11.5%

Ambient WindSpeed Max. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25845 
1
 
363

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25845
98.6%
1 363
 
1.4%

Length

2025-05-15T14:25:33.511489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:33.549278image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25845
98.6%
1 363
 
1.4%

Most occurring characters

ValueCountFrequency (%)
0 25845
98.6%
1 363
 
1.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25845
98.6%
1 363
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25845
98.6%
1 363
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25845
98.6%
1 363
 
1.4%

Ambient WindSpeed Min. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25692 
1
 
516

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25692
98.0%
1 516
 
2.0%

Length

2025-05-15T14:25:33.592128image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:33.628063image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25692
98.0%
1 516
 
2.0%

Most occurring characters

ValueCountFrequency (%)
0 25692
98.0%
1 516
 
2.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25692
98.0%
1 516
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25692
98.0%
1 516
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25692
98.0%
1 516
 
2.0%

Ambient WindSpeed Avg. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25918 
1
 
290

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25918
98.9%
1 290
 
1.1%

Length

2025-05-15T14:25:33.672141image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:33.708276image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25918
98.9%
1 290
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 25918
98.9%
1 290
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25918
98.9%
1 290
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25918
98.9%
1 290
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25918
98.9%
1 290
 
1.1%

Ambient WindSpeed StdDev [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24816 
1
 
1392

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24816
94.7%
1 1392
 
5.3%

Length

2025-05-15T14:25:33.750983image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:33.788739image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24816
94.7%
1 1392
 
5.3%

Most occurring characters

ValueCountFrequency (%)
0 24816
94.7%
1 1392
 
5.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24816
94.7%
1 1392
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24816
94.7%
1 1392
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24816
94.7%
1 1392
 
5.3%

Ambient WindDir Relative Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25528 
1
 
680

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25528
97.4%
1 680
 
2.6%

Length

2025-05-15T14:25:33.831284image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:33.867534image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25528
97.4%
1 680
 
2.6%

Most occurring characters

ValueCountFrequency (%)
0 25528
97.4%
1 680
 
2.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25528
97.4%
1 680
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25528
97.4%
1 680
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25528
97.4%
1 680
 
2.6%

Ambient WindDir Absolute Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25600 
1
 
608

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25600
97.7%
1 608
 
2.3%

Length

2025-05-15T14:25:33.912728image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:33.948627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25600
97.7%
1 608
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 25600
97.7%
1 608
 
2.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25600
97.7%
1 608
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25600
97.7%
1 608
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25600
97.7%
1 608
 
2.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22965 
1
3243 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22965
87.6%
1 3243
 
12.4%

Length

2025-05-15T14:25:33.991169image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:34.029398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22965
87.6%
1 3243
 
12.4%

Most occurring characters

ValueCountFrequency (%)
0 22965
87.6%
1 3243
 
12.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22965
87.6%
1 3243
 
12.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22965
87.6%
1 3243
 
12.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22965
87.6%
1 3243
 
12.4%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:34.073766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:34.107397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24750 
1
 
1458

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24750
94.4%
1 1458
 
5.6%

Length

2025-05-15T14:25:34.148449image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:34.184521image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24750
94.4%
1 1458
 
5.6%

Most occurring characters

ValueCountFrequency (%)
0 24750
94.4%
1 1458
 
5.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24750
94.4%
1 1458
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24750
94.4%
1 1458
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24750
94.4%
1 1458
 
5.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24171 
1
 
2037

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24171
92.2%
1 2037
 
7.8%

Length

2025-05-15T14:25:34.226628image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:34.413538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24171
92.2%
1 2037
 
7.8%

Most occurring characters

ValueCountFrequency (%)
0 24171
92.2%
1 2037
 
7.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24171
92.2%
1 2037
 
7.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24171
92.2%
1 2037
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24171
92.2%
1 2037
 
7.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23706 
1
2502 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Length

2025-05-15T14:25:34.456091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:34.492764image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Most occurring characters

ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23924 
1
 
2284

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23924
91.3%
1 2284
 
8.7%

Length

2025-05-15T14:25:34.538749image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:34.575465image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23924
91.3%
1 2284
 
8.7%

Most occurring characters

ValueCountFrequency (%)
0 23924
91.3%
1 2284
 
8.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23924
91.3%
1 2284
 
8.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23924
91.3%
1 2284
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23924
91.3%
1 2284
 
8.7%

Grid Production Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25397 
1
 
811

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25397
96.9%
1 811
 
3.1%

Length

2025-05-15T14:25:34.620144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:34.657791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25397
96.9%
1 811
 
3.1%

Most occurring characters

ValueCountFrequency (%)
0 25397
96.9%
1 811
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25397
96.9%
1 811
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25397
96.9%
1 811
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25397
96.9%
1 811
 
3.1%

Grid Production CosPhi Avg.
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25022 
1
 
1186

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25022
95.5%
1 1186
 
4.5%

Length

2025-05-15T14:25:34.700678image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:34.736630image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25022
95.5%
1 1186
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 25022
95.5%
1 1186
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25022
95.5%
1 1186
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25022
95.5%
1 1186
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25022
95.5%
1 1186
 
4.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26064 
1
 
144

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26064
99.5%
1 144
 
0.5%

Length

2025-05-15T14:25:34.781120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:34.817441image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26064
99.5%
1 144
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26064
99.5%
1 144
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26064
99.5%
1 144
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26064
99.5%
1 144
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26064
99.5%
1 144
 
0.5%

Grid Production VoltagePhase1 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25964 
1
 
244

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25964
99.1%
1 244
 
0.9%

Length

2025-05-15T14:25:34.861391image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:34.897555image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25964
99.1%
1 244
 
0.9%

Most occurring characters

ValueCountFrequency (%)
0 25964
99.1%
1 244
 
0.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25964
99.1%
1 244
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25964
99.1%
1 244
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25964
99.1%
1 244
 
0.9%

Grid Production VoltagePhase2 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25933 
1
 
275

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25933
99.0%
1 275
 
1.0%

Length

2025-05-15T14:25:34.939904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:34.977458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25933
99.0%
1 275
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25933
99.0%
1 275
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25933
99.0%
1 275
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25933
99.0%
1 275
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25933
99.0%
1 275
 
1.0%

Grid Production VoltagePhase3 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25939 
1
 
269

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25939
99.0%
1 269
 
1.0%

Length

2025-05-15T14:25:35.020914image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:35.057157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25939
99.0%
1 269
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25939
99.0%
1 269
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25939
99.0%
1 269
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25939
99.0%
1 269
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25939
99.0%
1 269
 
1.0%

Grid Production CurrentPhase1 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25347 
1
 
861

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25347
96.7%
1 861
 
3.3%

Length

2025-05-15T14:25:35.101500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:35.137634image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25347
96.7%
1 861
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25347
96.7%
1 861
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25347
96.7%
1 861
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25347
96.7%
1 861
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25347
96.7%
1 861
 
3.3%

Grid Production CurrentPhase2 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25324 
1
 
884

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25324
96.6%
1 884
 
3.4%

Length

2025-05-15T14:25:35.181636image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:35.219334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25324
96.6%
1 884
 
3.4%

Most occurring characters

ValueCountFrequency (%)
0 25324
96.6%
1 884
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25324
96.6%
1 884
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25324
96.6%
1 884
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25324
96.6%
1 884
 
3.4%

Grid Production CurrentPhase3 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25378 
1
 
830

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25378
96.8%
1 830
 
3.2%

Length

2025-05-15T14:25:35.262233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:35.298380image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25378
96.8%
1 830
 
3.2%

Most occurring characters

ValueCountFrequency (%)
0 25378
96.8%
1 830
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25378
96.8%
1 830
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25378
96.8%
1 830
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25378
96.8%
1 830
 
3.2%

Grid Production Power Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25023 
1
 
1185

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25023
95.5%
1 1185
 
4.5%

Length

2025-05-15T14:25:35.343743image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:35.379795image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25023
95.5%
1 1185
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 25023
95.5%
1 1185
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25023
95.5%
1 1185
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25023
95.5%
1 1185
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25023
95.5%
1 1185
 
4.5%

Grid Production Power Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25097 
1
 
1111

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25097
95.8%
1 1111
 
4.2%

Length

2025-05-15T14:25:35.422050image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:35.459790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25097
95.8%
1 1111
 
4.2%

Most occurring characters

ValueCountFrequency (%)
0 25097
95.8%
1 1111
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25097
95.8%
1 1111
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25097
95.8%
1 1111
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25097
95.8%
1 1111
 
4.2%

Grid Busbar Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24530 
1
 
1678

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24530
93.6%
1 1678
 
6.4%

Length

2025-05-15T14:25:35.502515image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:35.538406image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24530
93.6%
1 1678
 
6.4%

Most occurring characters

ValueCountFrequency (%)
0 24530
93.6%
1 1678
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24530
93.6%
1 1678
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24530
93.6%
1 1678
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24530
93.6%
1 1678
 
6.4%

Grid Production Power StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25033 
1
 
1175

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25033
95.5%
1 1175
 
4.5%

Length

2025-05-15T14:25:35.582654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:35.618766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25033
95.5%
1 1175
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 25033
95.5%
1 1175
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25033
95.5%
1 1175
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25033
95.5%
1 1175
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25033
95.5%
1 1175
 
4.5%

Grid Production ReactivePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24293 
1
 
1915

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24293
92.7%
1 1915
 
7.3%

Length

2025-05-15T14:25:35.661348image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:35.699300image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24293
92.7%
1 1915
 
7.3%

Most occurring characters

ValueCountFrequency (%)
0 24293
92.7%
1 1915
 
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24293
92.7%
1 1915
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24293
92.7%
1 1915
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24293
92.7%
1 1915
 
7.3%

Grid Production ReactivePower Max. [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22625 
1
3583 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22625
86.3%
1 3583
 
13.7%

Length

2025-05-15T14:25:35.741954image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:35.778409image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22625
86.3%
1 3583
 
13.7%

Most occurring characters

ValueCountFrequency (%)
0 22625
86.3%
1 3583
 
13.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22625
86.3%
1 3583
 
13.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22625
86.3%
1 3583
 
13.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22625
86.3%
1 3583
 
13.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23106 
1
3102 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23106
88.2%
1 3102
 
11.8%

Length

2025-05-15T14:25:35.825535image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:35.862707image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23106
88.2%
1 3102
 
11.8%

Most occurring characters

ValueCountFrequency (%)
0 23106
88.2%
1 3102
 
11.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23106
88.2%
1 3102
 
11.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23106
88.2%
1 3102
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23106
88.2%
1 3102
 
11.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
21656 
1
4552 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21656
82.6%
1 4552
 
17.4%

Length

2025-05-15T14:25:35.907300image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:35.945826image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 21656
82.6%
1 4552
 
17.4%

Most occurring characters

ValueCountFrequency (%)
0 21656
82.6%
1 4552
 
17.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 21656
82.6%
1 4552
 
17.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 21656
82.6%
1 4552
 
17.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 21656
82.6%
1 4552
 
17.4%

Grid Production PossiblePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25468 
1
 
740

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25468
97.2%
1 740
 
2.8%

Length

2025-05-15T14:25:35.990750image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:36.026927image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25468
97.2%
1 740
 
2.8%

Most occurring characters

ValueCountFrequency (%)
0 25468
97.2%
1 740
 
2.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25468
97.2%
1 740
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25468
97.2%
1 740
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25468
97.2%
1 740
 
2.8%

Grid Production PossiblePower Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25270 
1
 
938

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25270
96.4%
1 938
 
3.6%

Length

2025-05-15T14:25:36.071752image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:36.107805image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25270
96.4%
1 938
 
3.6%

Most occurring characters

ValueCountFrequency (%)
0 25270
96.4%
1 938
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25270
96.4%
1 938
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25270
96.4%
1 938
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25270
96.4%
1 938
 
3.6%

Grid Production PossiblePower Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25239 
1
 
969

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25239
96.3%
1 969
 
3.7%

Length

2025-05-15T14:25:36.150552image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:36.188353image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25239
96.3%
1 969
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25239
96.3%
1 969
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25239
96.3%
1 969
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25239
96.3%
1 969
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25239
96.3%
1 969
 
3.7%

Grid Production PossiblePower StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25358 
1
 
850

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25358
96.8%
1 850
 
3.2%

Length

2025-05-15T14:25:36.230896image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:36.267034image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25358
96.8%
1 850
 
3.2%

Most occurring characters

ValueCountFrequency (%)
0 25358
96.8%
1 850
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25358
96.8%
1 850
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25358
96.8%
1 850
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25358
96.8%
1 850
 
3.2%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:36.311908image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:36.345934image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:36.385717image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:36.421133image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:36.460637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:36.494409image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:36.535866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:36.569673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:36.609485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:36.644767image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:36.684265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:36.718197image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:36.759976image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:36.793927image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:36.833736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:36.869195image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Active power limit [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26166 
1
 
42

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26166
99.8%
1 42
 
0.2%

Length

2025-05-15T14:25:36.909118image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:36.945087image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26166
99.8%
1 42
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 26166
99.8%
1 42
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26166
99.8%
1 42
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26166
99.8%
1 42
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26166
99.8%
1 42
 
0.2%

Active power limit source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26200 
1
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Length

2025-05-15T14:25:36.989702image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:37.025751image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Reactive power set point [var]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:37.068436image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:37.104027image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Power factor set point
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26200 
1
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Length

2025-05-15T14:25:37.143735image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:37.179820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Power factor set point source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26200 
1
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Length

2025-05-15T14:25:37.377567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:37.413519image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Controller Ground Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25881 
1
 
327

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25881
98.8%
1 327
 
1.2%

Length

2025-05-15T14:25:37.455870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:37.493716image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25881
98.8%
1 327
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 25881
98.8%
1 327
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25881
98.8%
1 327
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25881
98.8%
1 327
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25881
98.8%
1 327
 
1.2%

Controller Top Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24949 
1
 
1259

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24949
95.2%
1 1259
 
4.8%

Length

2025-05-15T14:25:37.536065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:37.572009image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24949
95.2%
1 1259
 
4.8%

Most occurring characters

ValueCountFrequency (%)
0 24949
95.2%
1 1259
 
4.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24949
95.2%
1 1259
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24949
95.2%
1 1259
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24949
95.2%
1 1259
 
4.8%

Controller Hub Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25264 
1
 
944

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25264
96.4%
1 944
 
3.6%

Length

2025-05-15T14:25:37.616309image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:37.652211image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25264
96.4%
1 944
 
3.6%

Most occurring characters

ValueCountFrequency (%)
0 25264
96.4%
1 944
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25264
96.4%
1 944
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25264
96.4%
1 944
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25264
96.4%
1 944
 
3.6%

Controller VCP Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24100 
1
 
2108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24100
92.0%
1 2108
 
8.0%

Length

2025-05-15T14:25:37.694738image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:37.733679image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24100
92.0%
1 2108
 
8.0%

Most occurring characters

ValueCountFrequency (%)
0 24100
92.0%
1 2108
 
8.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24100
92.0%
1 2108
 
8.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24100
92.0%
1 2108
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24100
92.0%
1 2108
 
8.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25342 
1
 
866

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25342
96.7%
1 866
 
3.3%

Length

2025-05-15T14:25:37.778470image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:37.814796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25342
96.7%
1 866
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25342
96.7%
1 866
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25342
96.7%
1 866
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25342
96.7%
1 866
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25342
96.7%
1 866
 
3.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23223 
1
2985 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23223
88.6%
1 2985
 
11.4%

Length

2025-05-15T14:25:37.859654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:37.896569image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23223
88.6%
1 2985
 
11.4%

Most occurring characters

ValueCountFrequency (%)
0 23223
88.6%
1 2985
 
11.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23223
88.6%
1 2985
 
11.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23223
88.6%
1 2985
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23223
88.6%
1 2985
 
11.4%

Spinner Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23529 
1
2679 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23529
89.8%
1 2679
 
10.2%

Length

2025-05-15T14:25:37.943153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:37.980005image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23529
89.8%
1 2679
 
10.2%

Most occurring characters

ValueCountFrequency (%)
0 23529
89.8%
1 2679
 
10.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23529
89.8%
1 2679
 
10.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23529
89.8%
1 2679
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23529
89.8%
1 2679
 
10.2%

Spinner Temp. SlipRing Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:38.024896image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:38.058663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Blades PitchAngle Min. [°]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24035 
1
 
2173

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24035
91.7%
1 2173
 
8.3%

Length

2025-05-15T14:25:38.100796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:38.137743image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24035
91.7%
1 2173
 
8.3%

Most occurring characters

ValueCountFrequency (%)
0 24035
91.7%
1 2173
 
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24035
91.7%
1 2173
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24035
91.7%
1 2173
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24035
91.7%
1 2173
 
8.3%

Blades PitchAngle Max. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24002 
1
 
2206

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24002
91.6%
1 2206
 
8.4%

Length

2025-05-15T14:25:38.184176image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:38.220993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24002
91.6%
1 2206
 
8.4%

Most occurring characters

ValueCountFrequency (%)
0 24002
91.6%
1 2206
 
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24002
91.6%
1 2206
 
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24002
91.6%
1 2206
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24002
91.6%
1 2206
 
8.4%

Blades PitchAngle Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24111 
1
 
2097

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24111
92.0%
1 2097
 
8.0%

Length

2025-05-15T14:25:38.265506image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:38.304176image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24111
92.0%
1 2097
 
8.0%

Most occurring characters

ValueCountFrequency (%)
0 24111
92.0%
1 2097
 
8.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24111
92.0%
1 2097
 
8.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24111
92.0%
1 2097
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24111
92.0%
1 2097
 
8.0%

Blades PitchAngle StdDev [°]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23087 
1
3121 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23087
88.1%
1 3121
 
11.9%

Length

2025-05-15T14:25:38.349446image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:38.386926image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23087
88.1%
1 3121
 
11.9%

Most occurring characters

ValueCountFrequency (%)
0 23087
88.1%
1 3121
 
11.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23087
88.1%
1 3121
 
11.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23087
88.1%
1 3121
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23087
88.1%
1 3121
 
11.9%

HVTrafo Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25477 
1
 
731

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25477
97.2%
1 731
 
2.8%

Length

2025-05-15T14:25:38.433786image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:38.470064image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25477
97.2%
1 731
 
2.8%

Most occurring characters

ValueCountFrequency (%)
0 25477
97.2%
1 731
 
2.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25477
97.2%
1 731
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25477
97.2%
1 731
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25477
97.2%
1 731
 
2.8%

HVTrafo Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25446 
1
 
762

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25446
97.1%
1 762
 
2.9%

Length

2025-05-15T14:25:38.512698image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:38.550360image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25446
97.1%
1 762
 
2.9%

Most occurring characters

ValueCountFrequency (%)
0 25446
97.1%
1 762
 
2.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25446
97.1%
1 762
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25446
97.1%
1 762
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25446
97.1%
1 762
 
2.9%

HVTrafo Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25384 
1
 
824

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25384
96.9%
1 824
 
3.1%

Length

2025-05-15T14:25:38.593174image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:38.629599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25384
96.9%
1 824
 
3.1%

Most occurring characters

ValueCountFrequency (%)
0 25384
96.9%
1 824
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25384
96.9%
1 824
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25384
96.9%
1 824
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25384
96.9%
1 824
 
3.1%

HVTrafo AirOutlet Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23853 
1
 
2355

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23853
91.0%
1 2355
 
9.0%

Length

2025-05-15T14:25:38.674550image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:38.711375image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23853
91.0%
1 2355
 
9.0%

Most occurring characters

ValueCountFrequency (%)
0 23853
91.0%
1 2355
 
9.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23853
91.0%
1 2355
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23853
91.0%
1 2355
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23853
91.0%
1 2355
 
9.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:38.756171image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:38.791733image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

HourCounters Average GridOn Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26180 
1
 
28

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26180
99.9%
1 28
 
0.1%

Length

2025-05-15T14:25:38.832304image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:38.868534image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26180
99.9%
1 28
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26180
99.9%
1 28
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26180
99.9%
1 28
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26180
99.9%
1 28
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26180
99.9%
1 28
 
0.1%

HourCounters Average GridOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26176 
1
 
32

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26176
99.9%
1 32
 
0.1%

Length

2025-05-15T14:25:38.913188image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:38.949163image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26176
99.9%
1 32
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26176
99.9%
1 32
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26176
99.9%
1 32
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26176
99.9%
1 32
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26176
99.9%
1 32
 
0.1%

HourCounters Average TurbineOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26166 
1
 
42

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26166
99.8%
1 42
 
0.2%

Length

2025-05-15T14:25:38.992074image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:39.030302image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26166
99.8%
1 42
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 26166
99.8%
1 42
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26166
99.8%
1 42
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26166
99.8%
1 42
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26166
99.8%
1 42
 
0.2%

HourCounters Average Run Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26106 
1
 
102

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26106
99.6%
1 102
 
0.4%

Length

2025-05-15T14:25:39.073129image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:39.109418image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26106
99.6%
1 102
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26106
99.6%
1 102
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26106
99.6%
1 102
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26106
99.6%
1 102
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26106
99.6%
1 102
 
0.4%

HourCounters Average Gen1 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25473 
1
 
735

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25473
97.2%
1 735
 
2.8%

Length

2025-05-15T14:25:39.153780image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:39.190467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25473
97.2%
1 735
 
2.8%

Most occurring characters

ValueCountFrequency (%)
0 25473
97.2%
1 735
 
2.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25473
97.2%
1 735
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25473
97.2%
1 735
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25473
97.2%
1 735
 
2.8%

HourCounters Average Gen2 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24561 
1
 
1647

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24561
93.7%
1 1647
 
6.3%

Length

2025-05-15T14:25:39.233577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:39.271975image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24561
93.7%
1 1647
 
6.3%

Most occurring characters

ValueCountFrequency (%)
0 24561
93.7%
1 1647
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24561
93.7%
1 1647
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24561
93.7%
1 1647
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24561
93.7%
1 1647
 
6.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23090 
1
3118 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23090
88.1%
1 3118
 
11.9%

Length

2025-05-15T14:25:39.315375image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:39.352403image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23090
88.1%
1 3118
 
11.9%

Most occurring characters

ValueCountFrequency (%)
0 23090
88.1%
1 3118
 
11.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23090
88.1%
1 3118
 
11.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23090
88.1%
1 3118
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23090
88.1%
1 3118
 
11.9%

HourCounters Average ServiceOn Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26186 
1
 
22

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Length

2025-05-15T14:25:39.399627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:39.435768image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

HourCounters Average AmbientOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26133 
1
 
75

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26133
99.7%
1 75
 
0.3%

Length

2025-05-15T14:25:39.478281image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:39.516130image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26133
99.7%
1 75
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 26133
99.7%
1 75
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26133
99.7%
1 75
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26133
99.7%
1 75
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26133
99.7%
1 75
 
0.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24726 
1
 
1482

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24726
94.3%
1 1482
 
5.7%

Length

2025-05-15T14:25:39.558863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:39.595100image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24726
94.3%
1 1482
 
5.7%

Most occurring characters

ValueCountFrequency (%)
0 24726
94.3%
1 1482
 
5.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24726
94.3%
1 1482
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24726
94.3%
1 1482
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24726
94.3%
1 1482
 
5.7%

HourCounters Average AlarmActive Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26085 
1
 
123

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26085
99.5%
1 123
 
0.5%

Length

2025-05-15T14:25:39.639623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:39.675660image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26085
99.5%
1 123
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26085
99.5%
1 123
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26085
99.5%
1 123
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26085
99.5%
1 123
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26085
99.5%
1 123
 
0.5%

Total hour counter [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:39.718411image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:39.753807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid on hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:39.793745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:39.827458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:39.869399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:39.903345image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Turbine ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:39.942958image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:39.978639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Run hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:40.018421image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:40.052420image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 1 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:40.093847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:40.127619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 2 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:40.167124image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:40.202567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Yaw hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:40.242025image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:40.275907image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Service hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:40.317294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:40.511124image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Ambient ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:40.550372image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:40.585939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Wind ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:40.625618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:40.659174image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Production LatestAverage Active Power Gen 0 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25073 
1
 
1135

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25073
95.7%
1 1135
 
4.3%

Length

2025-05-15T14:25:40.701048image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:40.737033image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25073
95.7%
1 1135
 
4.3%

Most occurring characters

ValueCountFrequency (%)
0 25073
95.7%
1 1135
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25073
95.7%
1 1135
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25073
95.7%
1 1135
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25073
95.7%
1 1135
 
4.3%

Production LatestAverage Active Power Gen 1 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25547 
1
 
661

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25547
97.5%
1 661
 
2.5%

Length

2025-05-15T14:25:40.779922image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:40.818240image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25547
97.5%
1 661
 
2.5%

Most occurring characters

ValueCountFrequency (%)
0 25547
97.5%
1 661
 
2.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25547
97.5%
1 661
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25547
97.5%
1 661
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25547
97.5%
1 661
 
2.5%

Production LatestAverage Active Power Gen 2 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25230 
1
 
978

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25230
96.3%
1 978
 
3.7%

Length

2025-05-15T14:25:40.861255image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:40.897601image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25230
96.3%
1 978
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25230
96.3%
1 978
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25230
96.3%
1 978
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25230
96.3%
1 978
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25230
96.3%
1 978
 
3.7%

Production LatestAverage Total Active Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25401 
1
 
807

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25401
96.9%
1 807
 
3.1%

Length

2025-05-15T14:25:40.942572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:40.978841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25401
96.9%
1 807
 
3.1%

Most occurring characters

ValueCountFrequency (%)
0 25401
96.9%
1 807
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25401
96.9%
1 807
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25401
96.9%
1 807
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25401
96.9%
1 807
 
3.1%

Production LatestAverage Reactive Power Gen 0 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24988 
1
 
1220

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24988
95.3%
1 1220
 
4.7%

Length

2025-05-15T14:25:41.021462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:41.059824image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24988
95.3%
1 1220
 
4.7%

Most occurring characters

ValueCountFrequency (%)
0 24988
95.3%
1 1220
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24988
95.3%
1 1220
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24988
95.3%
1 1220
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24988
95.3%
1 1220
 
4.7%

Production LatestAverage Reactive Power Gen 1 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23991 
1
 
2217

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23991
91.5%
1 2217
 
8.5%

Length

2025-05-15T14:25:41.103158image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:41.139874image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23991
91.5%
1 2217
 
8.5%

Most occurring characters

ValueCountFrequency (%)
0 23991
91.5%
1 2217
 
8.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23991
91.5%
1 2217
 
8.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23991
91.5%
1 2217
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23991
91.5%
1 2217
 
8.5%

Production LatestAverage Reactive Power Gen 2 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24357 
1
 
1851

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24357
92.9%
1 1851
 
7.1%

Length

2025-05-15T14:25:41.186577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:41.222603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24357
92.9%
1 1851
 
7.1%

Most occurring characters

ValueCountFrequency (%)
0 24357
92.9%
1 1851
 
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24357
92.9%
1 1851
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24357
92.9%
1 1851
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24357
92.9%
1 1851
 
7.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22609 
1
3599 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22609
86.3%
1 3599
 
13.7%

Length

2025-05-15T14:25:41.266957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:41.303843image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22609
86.3%
1 3599
 
13.7%

Most occurring characters

ValueCountFrequency (%)
0 22609
86.3%
1 3599
 
13.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22609
86.3%
1 3599
 
13.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22609
86.3%
1 3599
 
13.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22609
86.3%
1 3599
 
13.7%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:41.348463image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:41.382189image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:41.423882image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:41.457625image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26201 
1
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Length

2025-05-15T14:25:41.499057image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:41.535221image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Total Active power [W]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26147 
1
 
61

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26147
99.8%
1 61
 
0.2%

Length

2025-05-15T14:25:41.577578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:41.613516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26147
99.8%
1 61
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 26147
99.8%
1 61
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26147
99.8%
1 61
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26147
99.8%
1 61
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26147
99.8%
1 61
 
0.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26090 
1
 
118

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26090
99.5%
1 118
 
0.5%

Length

2025-05-15T14:25:41.658212image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:41.694413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26090
99.5%
1 118
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26090
99.5%
1 118
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26090
99.5%
1 118
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26090
99.5%
1 118
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26090
99.5%
1 118
 
0.5%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:41.738955image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:41.772798image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:25:41.812572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:41.846342image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Total reactive power [var]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26087 
1
 
121

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26087
99.5%
1 121
 
0.5%

Length

2025-05-15T14:25:41.888320image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:25:41.924389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26087
99.5%
1 121
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26087
99.5%
1 121
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26087
99.5%
1 121
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26087
99.5%
1 121
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26087
99.5%
1 121
 
0.5%

Correlations

2025-05-15T14:25:42.053247image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Active power generator 2, Total accumulated [W]Active power limit [W]Active power limit sourceAmbient Temp. Avg. [°C]Ambient WindDir Absolute Avg. [°]Ambient WindDir Relative Avg. [°]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed StdDev [m/s]Blades PitchAngle Avg. [°]Blades PitchAngle Max. [°]Blades PitchAngle Min. [°]Blades PitchAngle StdDev [°]Controller Ground Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Generator Bearing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator RPM Avg. [RPM]Generator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM StdDev [RPM]Generator SlipRing Temp. Avg. [°C]Grid Busbar Temp. Avg. [°C]Grid InverterPhase1 Temp. Avg. [°C]Grid Production CosPhi Avg.Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Frequency Avg. [Hz]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production Power Avg. [W]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HourCounters Average AlarmActive Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average Yaw Avg. [h]Hydraulic Oil Temp. Avg. [°C]Nacelle Temp. Avg. [°C]Power factor set pointPower factor set point sourceProduction LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Total Reactive Power Avg. [var]Reactive power generator 0,Total accumulated [var]Rotor RPM Avg. [RPM]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM StdDev [RPM]Spinner Temp. Avg. [°C]Total Active power [W]Total reactive power [var]
Active power generator 2, Total accumulated [W]1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0160.0150.0150.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0140.0000.0170.0000.0140.0140.0000.0000.0000.0000.0000.0000.0000.0170.0000.0000.0290.0000.0120.0250.0120.0060.0160.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0240.0000.0270.0110.0000.0170.0000.0000.0000.0000.0130.0000.0110.0120.0000.000
Active power limit [W]0.0001.0000.4090.0110.0000.0060.0000.0000.0660.0000.0090.0270.0030.0300.1030.0140.0140.0000.0000.0080.0000.0050.0000.0000.0000.0000.0000.0020.0000.0020.0000.0000.0000.0000.0110.0000.0110.0050.0000.0050.0150.0160.0090.0100.0000.0120.0200.0000.0100.0100.0040.0000.0040.0300.0180.0270.0330.0000.0080.0000.0000.0050.0000.0000.0000.0000.0000.2970.3280.0120.0000.4770.7430.1280.3120.1770.0790.0000.0000.0170.4090.4090.0400.0060.0000.0290.0030.0000.0110.0120.0750.0120.0000.0000.0130.0000.0000.074
Active power limit source0.0000.4091.0000.0080.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0470.0250.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0250.0000.0000.0000.0000.0000.0000.0000.0270.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.2060.1420.0000.0000.2180.5010.0150.2630.0260.0380.0000.0000.0000.9370.9370.0000.0000.0000.0000.0000.0000.0000.0000.0470.0000.0000.0000.0000.0000.0000.079
Ambient Temp. Avg. [°C]0.0000.0110.0081.0000.0110.0080.0060.0180.0150.0010.0190.0340.0090.0090.0000.0100.0250.0120.0230.0270.0240.0060.0000.0340.0190.0190.0140.0020.0010.0000.0140.0100.0130.0240.0320.0060.0180.0270.0080.0080.0000.0240.0220.0300.0000.0240.0090.0200.0140.0250.0170.0200.0100.0080.0170.0000.0020.0150.0090.0150.0140.0120.0110.0090.0000.0000.0120.0060.0090.0000.0000.0060.0130.0000.0000.0030.0120.0000.0000.0410.0080.0080.0010.0190.0180.0200.0000.0000.0240.0120.0000.0130.0220.0000.0120.0210.0000.000
Ambient WindDir Absolute Avg. [°]0.0000.0000.0000.0111.0000.1290.0180.0390.0080.0000.0160.0120.0240.0140.0020.0000.0080.0000.0000.0000.0000.0090.0000.0000.0000.0000.0140.0000.0000.0080.0000.0090.0000.0230.0360.0190.0320.0120.0020.0110.0250.0000.0110.0130.0000.0000.0000.0030.0070.0030.0130.0000.0150.0300.0070.0160.0120.0060.0000.0000.0090.0000.0060.0000.0080.0000.0110.0120.0060.0150.0300.0000.0000.0110.0000.0000.0050.0070.0060.0000.0000.0000.0230.0000.0160.0360.0070.0220.0000.0100.0000.0190.0260.0120.0190.0000.0000.016
Ambient WindDir Relative Avg. [°]0.0000.0060.0170.0080.1291.0000.0120.0220.0000.0140.0870.0910.0640.0410.0160.0070.0000.0120.0000.0030.0080.0080.0040.0240.0190.0000.0720.0000.0000.0070.0020.0000.0000.0830.0990.0670.0860.0150.0000.0160.0780.0100.0000.0070.0000.0160.0040.0000.0000.0120.0000.0090.0000.0950.0510.0700.0290.0070.0120.0000.0000.0000.0000.0200.0050.0000.0000.0600.0610.0000.0900.0170.0190.0720.0000.0440.0060.0090.0000.0000.0170.0170.1340.0130.0060.1330.0220.0410.0130.0590.0330.0830.0800.0610.0670.0060.0070.000
Ambient WindSpeed Avg. [m/s]0.0000.0000.0000.0060.0180.0121.0000.1610.0750.0220.1290.0580.0490.0240.0000.0050.0000.0000.0000.0140.0790.0520.0820.0730.0720.0720.0090.0160.0110.0000.0430.0340.0340.1090.0860.0700.0700.0180.0000.0350.0320.2130.2030.2190.0000.2340.0770.0860.0410.2260.0640.0960.0370.0340.0270.0270.0200.0000.0000.0000.0290.0250.0350.0130.0100.0000.0000.0000.0000.0150.0410.0000.0000.0000.0000.0000.0360.0190.0080.0000.0000.0000.0440.0890.1240.0410.0000.0140.2230.0250.0000.1100.0750.0640.0510.0070.0000.000
Ambient WindSpeed Max. [m/s]0.0000.0000.0000.0180.0390.0220.1611.0000.0080.0330.0750.0550.0320.0260.0000.0090.0000.0000.0050.0000.0400.0270.0390.0460.0260.0310.0040.0060.0220.0030.0080.0170.0200.0520.0560.0340.0420.0130.0000.0190.0360.0720.0830.0990.0000.0850.0990.0450.0670.0810.0910.0500.0550.0360.0340.0290.0310.0000.0000.0110.0190.0230.0160.0090.0000.0100.0000.0000.0000.0220.0410.0000.0000.0000.0000.0000.0390.0060.0000.0000.0000.0000.0340.0360.0530.0310.0000.0040.0910.0210.0000.0460.0500.0310.0350.0240.0000.000
Ambient WindSpeed Min. [m/s]0.0000.0660.0000.0150.0080.0000.0750.0081.0000.0160.0720.0220.1130.0800.0160.0000.0080.0100.0000.0000.0460.0320.0280.0470.0280.0340.0000.0000.0000.0000.0140.0050.0120.0510.0440.0810.0480.0110.0000.0200.0260.0560.0550.0630.0000.0610.0320.0920.0350.0590.0310.0920.0470.0760.0550.0550.0560.0000.0050.0000.0200.0240.0200.0150.0000.0000.0030.0150.0410.0630.0550.0690.0830.0090.0190.0240.0570.0170.0210.0000.0000.0000.0280.0580.0550.0190.0200.0550.0630.0520.0060.0480.0290.0720.0340.0000.0040.006
Ambient WindSpeed StdDev [m/s]0.0100.0000.0000.0010.0000.0140.0220.0330.0161.0000.0350.0070.0330.0720.0010.0060.0000.0040.0000.0090.0170.0070.0150.0270.0160.0220.0000.0000.0000.0080.0450.0300.0410.0380.0300.0340.0710.0000.0030.0060.0280.0290.0360.0360.0070.0290.0260.0300.1190.0310.0310.0240.1190.0310.0240.0240.0210.0000.0000.0000.0270.0210.0260.0010.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0000.0050.0330.0080.0070.0000.0000.0240.0000.0140.0240.0190.0230.0270.0000.0000.0400.0270.0200.0520.0000.0000.000
Blades PitchAngle Avg. [°]0.0160.0090.0000.0190.0160.0870.1290.0750.0720.0351.0000.2130.4240.4360.0170.0000.0060.0220.0220.0030.0180.0410.0380.0630.1020.0550.0390.0220.0240.0000.0000.0000.0000.2140.2090.2250.2220.0420.0140.0220.2460.1530.1640.2000.0000.2070.1860.2330.2300.2140.1720.1780.2200.3760.2400.2160.2210.0000.0040.0000.0070.0210.0300.0300.0240.0010.0300.1450.0990.1400.3610.0400.0130.1610.0420.0990.0380.0880.0320.0000.0000.0000.3620.0600.2640.3150.0870.2350.2170.2710.0420.2280.1860.1800.1830.0150.0360.059
Blades PitchAngle Max. [°]0.0150.0270.0000.0340.0120.0910.0580.0550.0220.0070.2131.0000.1010.0620.0040.0000.0120.0070.0090.0070.0270.0240.0280.0470.0720.0300.0850.0040.0000.0000.0000.0000.0000.0690.2280.0360.0450.0320.0100.0000.1630.0840.0940.1250.0000.1360.1500.1200.1440.1310.1300.0740.1000.1520.1160.0620.0430.0040.0110.0090.0000.0150.0000.0130.0000.0070.0000.0800.0770.0210.1420.0340.0250.0900.0260.0650.1570.0300.0110.0100.0000.0000.2090.0180.1120.2080.0230.0560.1320.1080.0000.0680.1940.0510.0460.0060.0580.000
Blades PitchAngle Min. [°]0.0150.0030.0000.0090.0240.0640.0490.0320.1130.0330.4240.1011.0000.5600.0030.0000.0000.0060.0240.0050.0360.0590.0240.0570.0750.0410.0050.0190.0350.0130.0000.0000.0000.2230.1670.3580.2450.0390.0140.0080.3320.1110.1210.1430.0000.1580.1380.1910.1940.1690.1220.1600.1970.6330.4340.3490.3920.0000.0000.0000.0170.0240.0230.0310.0290.0330.0350.1260.0780.3140.5380.0390.0070.1440.0310.1000.0440.0430.0180.0080.0000.0000.4410.1710.2890.3940.2010.4570.1720.4510.0550.2300.1420.2950.2010.0000.0350.048
Blades PitchAngle StdDev [°]0.0180.0300.0000.0090.0140.0410.0240.0260.0800.0720.4360.0620.5601.0000.0090.0130.0040.0330.0290.0000.0000.0170.0060.0110.0400.0260.0000.0270.0120.0000.0030.0000.0000.1520.1440.2320.3650.0220.0110.0110.2720.0820.0970.1140.0000.1520.1390.2650.2220.1320.1110.1880.2280.4800.3290.2710.3950.0000.0000.0000.0160.0140.0130.0160.0350.0300.0350.1150.0910.2400.4120.0530.0250.1010.0400.0540.0140.1170.0270.0020.0000.0000.3180.1170.2590.2860.1670.4740.1360.3370.0800.1600.1260.1750.3020.0000.0590.089
Controller Ground Temp. Avg. [°C]0.0000.1030.0470.0000.0020.0160.0000.0000.0160.0010.0170.0040.0030.0091.0000.0080.0000.0110.0080.0040.0000.0020.0000.0000.0030.0060.0000.0000.0080.0000.0000.0000.0000.0000.0000.0150.0140.0090.0000.0080.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0080.0100.0140.0040.0150.0160.0000.0040.0000.0000.0000.0000.0000.0110.0550.0480.0000.0000.0800.1280.0340.0500.0340.0120.0210.0000.0000.0470.0470.0150.0080.0070.0160.0000.0080.0000.0000.0080.0000.0000.0190.0060.0110.0000.014
Controller Hub Temp. Avg. [°C]0.0000.0140.0250.0100.0000.0070.0050.0090.0000.0060.0000.0000.0000.0130.0081.0000.0060.0060.0080.0000.0000.0060.0070.0130.0080.0100.0180.0170.0080.0000.0080.0090.0000.0040.0140.0020.0170.0130.0080.0090.0150.0180.0230.0180.0000.0090.0160.0110.0000.0100.0270.0250.0000.0290.0080.0000.0220.0000.0000.0000.0010.0100.0000.0000.0000.0000.0050.0390.0410.0330.0140.0250.0210.0420.0000.0300.0000.0000.0130.0000.0250.0250.0090.0140.0150.0140.0000.0180.0120.0150.0000.0060.0110.0000.0110.0820.0080.000
Controller Top Temp. Avg. [°C]0.0000.0140.0100.0250.0080.0000.0000.0000.0080.0000.0060.0120.0000.0040.0000.0061.0000.0000.0520.0120.0030.0000.0000.0000.0000.0000.0040.0270.0220.0110.0150.0100.0220.0100.0000.0000.0040.0000.0000.0040.0120.0100.0000.0000.0000.0060.0000.0130.0000.0000.0080.0000.0000.0080.0000.0000.0030.0150.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0030.0080.0220.0040.0000.0140.0080.0000.0080.0150.0100.0100.0140.0090.0060.0150.0100.0000.0000.0000.0060.0100.0000.0060.0000.0160.0000.000
Controller VCP ChokecoilTemp. Avg. [°C]0.0000.0000.0000.0120.0000.0120.0000.0000.0100.0040.0220.0070.0060.0330.0110.0060.0001.0000.0230.0110.0550.0350.0300.0310.0340.0500.0100.0240.0060.0170.0490.0560.0400.0130.0000.0060.0200.0000.0140.0310.0260.0090.0080.0060.0000.0000.0140.0000.0000.0000.0180.0040.0120.0000.0000.0050.0000.0000.0000.0000.0270.0250.0350.0060.0000.0120.0210.0050.0050.0250.0000.0000.0000.0020.0000.0000.0000.0180.0250.0180.0000.0000.0190.0120.0100.0210.0130.0160.0000.0000.0090.0060.0000.0080.0230.0000.0030.009
Controller VCP Temp. Avg. [°C]0.0000.0000.0000.0230.0000.0000.0000.0050.0000.0000.0220.0090.0240.0290.0080.0080.0520.0231.0000.0050.0140.0000.0120.0160.0100.0400.0100.0480.0250.0250.0000.0090.0000.0210.0090.0290.0210.0480.0420.0000.0110.0000.0000.0000.0000.0170.0130.0270.0200.0150.0030.0090.0060.0220.0090.0140.0140.0000.0000.0000.0100.0000.0000.0240.0350.0360.0400.0140.0000.0170.0240.0100.0070.0220.0000.0350.0000.0110.0050.0530.0000.0000.0180.0230.0170.0130.0120.0280.0220.0260.0000.0210.0130.0240.0240.0070.0000.003
Controller VCP WaterTemp. Avg. [°C]0.0000.0080.0000.0270.0000.0030.0140.0000.0000.0090.0030.0070.0050.0000.0040.0000.0120.0110.0051.0000.0380.0420.0290.0480.0320.0430.0060.0180.0100.2650.0400.0520.0400.0220.0110.0090.0170.0280.0000.1580.0000.0060.0290.0310.0000.0110.0000.0000.0160.0160.0090.0000.0120.0040.0000.0070.0040.0000.0000.0000.1970.2550.2080.0050.0110.0130.0140.0000.0020.0000.0000.0000.0000.0000.0000.0000.0210.0000.0000.0000.0000.0000.0000.0050.0000.0140.0150.0000.0160.0000.0000.0170.0150.0240.0070.0000.0000.013
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]0.0000.0000.0000.0240.0000.0080.0790.0400.0460.0170.0180.0270.0360.0000.0000.0000.0030.0550.0140.0381.0000.2020.2720.2830.1950.2390.0480.0420.0480.0330.0900.1020.0690.1160.0520.0650.0670.0560.0060.0360.0310.0630.0700.0680.0000.0700.0510.0280.0260.0780.0470.0170.0210.0110.0300.0330.0170.0000.0030.0000.0560.0550.0650.0180.0000.0060.0000.0040.0070.0000.0230.0000.0000.0100.0000.0000.0250.0060.0240.0090.0000.0000.0440.0570.0000.0400.0060.0000.0760.0290.0000.1030.0600.0660.0670.0310.0080.009
Gear Bearing TemperatureHSMiddle Avg. [°C]0.0000.0050.0000.0060.0090.0080.0520.0270.0320.0070.0410.0240.0590.0170.0020.0060.0000.0350.0000.0420.2021.0000.1130.2350.2500.1760.0170.0530.0250.0430.1010.0950.0930.1580.0970.0930.0980.0510.0190.0350.0320.0630.0580.0670.0000.0490.0300.0290.0310.0590.0360.0240.0300.0320.0240.0410.0080.0000.0000.0000.0510.0630.0670.0230.0240.0090.0190.0110.0150.0060.0480.0010.0000.0160.0000.0050.0140.0000.0140.0000.0000.0000.0620.0510.0000.0510.0100.0180.0610.0190.0430.1400.0840.1050.0940.0140.0030.017
Gear Bearing TemperatureHSRotorEnd Avg. [°C]0.0000.0000.0000.0000.0000.0040.0820.0390.0280.0150.0380.0280.0240.0060.0000.0070.0000.0300.0120.0290.2720.1131.0000.1980.1470.2250.0340.0440.0220.0120.0670.0560.0580.1190.0480.0630.0730.0330.0000.0370.0000.0630.0550.0630.0100.0550.0470.0210.0360.0600.0330.0200.0280.0000.0080.0200.0000.0000.0000.0000.0230.0310.0300.0150.0120.0150.0090.0300.0210.0000.0090.0000.0000.0360.0000.0160.0110.0000.0210.0100.0000.0000.0340.0270.0160.0290.0000.0160.0640.0100.0000.1180.0720.0660.0480.0140.0000.004
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]0.0000.0000.0000.0340.0000.0240.0730.0460.0470.0270.0630.0470.0570.0110.0000.0130.0000.0310.0160.0480.2830.2350.1981.0000.2170.2030.0280.0350.0210.0510.0950.0900.0690.1280.0630.0760.0670.0570.0130.0410.0350.0700.0680.0810.0000.0700.0400.0420.0360.0770.0450.0260.0230.0300.0300.0370.0150.0000.0000.0000.0660.0620.0640.0230.0000.0130.0000.0180.0120.0000.0410.0000.0000.0240.0000.0030.0470.0000.0160.0200.0000.0000.0640.0510.0090.0580.0000.0000.0760.0340.0040.1200.0730.0900.0680.0390.0000.011
Gear Bearing TemperatureHollowShaftRotor Avg. [°C]0.0000.0000.0000.0190.0000.0190.0720.0260.0280.0160.1020.0720.0750.0400.0030.0080.0000.0340.0100.0320.1950.2500.1470.2171.0000.2130.0460.0630.0330.0330.0960.0850.0710.1700.0960.1070.0950.0520.0270.0210.0550.0410.0270.0390.0040.0420.0380.0390.0330.0550.0260.0120.0230.0610.0490.0450.0300.0000.0010.0000.0320.0420.0540.0180.0210.0140.0140.0070.0000.0180.0830.0000.0000.0130.0020.0010.0310.0000.0090.0290.0000.0000.0950.0380.0100.0840.0130.0160.0470.0590.0180.1540.0870.1120.0780.0340.0000.000
Gear Oil TemperatureBasis Avg. [°C]0.0000.0000.0000.0190.0000.0000.0720.0310.0340.0220.0550.0300.0410.0260.0060.0100.0000.0500.0400.0430.2390.1760.2250.2030.2131.0000.0380.0580.0300.0530.1100.0980.0980.1380.0830.0720.0890.0580.0080.0000.0300.0360.0340.0380.0000.0330.0500.0300.0380.0360.0360.0190.0200.0210.0240.0370.0000.0000.0000.0000.0210.0410.0370.0170.0070.0000.0140.0070.0000.0110.0340.0000.0000.0120.0000.0000.0660.0080.0200.0080.0000.0000.0620.0030.0030.0530.0130.0110.0380.0160.0050.1380.0880.0860.0720.0120.0000.010
Gear Oil TemperatureLevel1 Avg. [°C]0.0000.0000.0000.0140.0140.0720.0090.0040.0000.0000.0390.0850.0050.0000.0000.0180.0040.0100.0100.0060.0480.0170.0340.0280.0460.0381.0000.0000.0150.0090.0000.0000.0090.0450.0940.0190.0560.0080.0150.0100.0440.0370.0410.0390.0000.0630.0720.0450.0340.0630.0680.0400.0330.0280.0110.0280.0470.0000.0000.0070.0100.0200.0140.0190.0000.0080.0000.0640.0430.0190.0250.0130.0100.0740.0000.0440.0350.0000.0110.0210.0000.0000.0720.0230.0080.0740.0250.0190.0630.0570.0050.0350.0740.0000.0820.0400.0290.006
Generator Bearing Temp. Avg. [°C]0.0000.0020.0000.0020.0000.0000.0160.0060.0000.0000.0220.0040.0190.0270.0000.0170.0270.0240.0480.0180.0420.0530.0440.0350.0630.0580.0001.0000.0680.0210.0470.0310.0400.0280.0310.0320.0250.0230.0070.0000.0150.0360.0350.0280.0000.0280.0060.0180.0280.0280.0000.0340.0170.0270.0120.0120.0210.0000.0040.0000.0090.0040.0280.0110.0400.0310.0540.0090.0030.0380.0480.0000.0000.0070.0000.0020.0170.0110.0190.0140.0000.0000.0240.0340.0330.0170.0000.0380.0320.0140.0000.0360.0240.0270.0220.0000.0000.000
Generator Bearing2 Temp. Avg. [°C]0.0000.0000.0000.0010.0000.0000.0110.0220.0000.0000.0240.0000.0350.0120.0080.0080.0220.0060.0250.0100.0480.0250.0220.0210.0330.0300.0150.0681.0000.0150.0540.0280.0420.0260.0220.0350.0250.0000.0220.0130.0180.0310.0140.0240.0000.0290.0090.0180.0180.0330.0060.0210.0210.0280.0210.0230.0270.0000.0060.0070.0000.0000.0000.0050.0280.0410.0290.0000.0000.0140.0360.0000.0000.0000.0000.0000.0000.0000.0000.0250.0000.0000.0310.0140.0220.0280.0070.0270.0240.0270.0000.0210.0210.0340.0280.0000.0120.000
Generator CoolingWater Temp. Avg. [°C]0.0000.0020.0000.0000.0080.0070.0000.0030.0000.0080.0000.0000.0130.0000.0000.0000.0110.0170.0250.2650.0330.0430.0120.0510.0330.0530.0090.0210.0151.0000.0520.0440.0320.0300.0140.0140.0170.0310.0000.0910.0100.0040.0180.0150.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0020.0070.0000.0060.0130.0150.1430.1620.1590.0200.0240.0180.0380.0000.0000.0000.0070.0000.0000.0000.0000.0000.0240.0090.0000.0000.0000.0000.0010.0000.0000.0180.0200.0000.0000.0000.0000.0280.0110.0320.0080.0170.0000.000
Generator Phase1 Temp. Avg. [°C]0.0000.0000.0000.0140.0000.0020.0430.0080.0140.0450.0000.0000.0000.0030.0000.0080.0150.0490.0000.0400.0900.1010.0670.0950.0960.1100.0000.0470.0540.0521.0000.3200.3930.0430.0350.0070.0380.0080.0100.0840.0260.0460.0550.0520.0000.0420.0120.0000.0260.0330.0430.0100.0470.0130.0310.0000.0000.0000.0200.0120.0530.0670.0670.0030.0270.0220.0180.0050.0080.0280.0000.0000.0000.0000.0000.0010.0120.0000.0000.0030.0000.0000.0260.0080.0120.0330.0410.0000.0370.0130.0000.0370.0190.0000.0200.0130.0030.005
Generator Phase2 Temp. Avg. [°C]0.0140.0000.0000.0100.0090.0000.0340.0170.0050.0300.0000.0000.0000.0000.0000.0090.0100.0560.0090.0520.1020.0950.0560.0900.0850.0980.0000.0310.0280.0440.3201.0000.4390.0430.0280.0010.0310.0070.0000.0730.0190.0310.0470.0420.0050.0400.0120.0000.0340.0410.0400.0020.0430.0000.0310.0180.0000.0000.0000.0000.0660.0620.0820.0000.0250.0280.0250.0000.0000.0220.0000.0000.0000.0000.0000.0000.0200.0060.0010.0030.0000.0000.0160.0000.0180.0270.0390.0000.0410.0100.0070.0370.0210.0080.0120.0060.0000.007
Generator Phase3 Temp. Avg. [°C]0.0140.0000.0000.0130.0000.0000.0340.0200.0120.0410.0000.0000.0000.0000.0000.0000.0220.0400.0000.0400.0690.0930.0580.0690.0710.0980.0090.0400.0420.0320.3930.4391.0000.0260.0400.0060.0310.0000.0170.0760.0230.0380.0430.0430.0000.0330.0160.0000.0320.0280.0510.0100.0450.0000.0190.0170.0000.0000.0140.0190.0660.0590.0690.0120.0080.0180.0020.0110.0060.0270.0000.0000.0000.0090.0000.0000.0110.0050.0080.0000.0000.0000.0140.0090.0100.0270.0420.0090.0290.0160.0100.0260.0200.0150.0160.0120.0000.010
Generator RPM Avg. [RPM]0.0000.0000.0000.0240.0230.0830.1090.0520.0510.0380.2140.0690.2230.1520.0000.0040.0100.0130.0210.0220.1160.1580.1190.1280.1700.1380.0450.0280.0260.0300.0430.0430.0261.0000.3990.3600.4660.0570.0060.0000.1860.1320.1450.1630.0000.1510.1700.1420.1650.1600.1510.0950.1440.1990.1180.1530.0970.0080.0000.0000.0100.0270.0270.0270.0050.0000.0130.0990.0770.0370.2230.0170.0000.1120.0200.0520.0000.0250.0000.0030.0000.0000.2850.0550.0940.2690.0000.1170.1640.1480.0590.7080.3690.3360.4020.0270.0300.052
Generator RPM Max. [RPM]0.0170.0110.0000.0320.0360.0990.0860.0560.0440.0300.2090.2280.1670.1440.0000.0140.0000.0000.0090.0110.0520.0970.0480.0630.0960.0830.0940.0310.0220.0140.0350.0280.0400.3991.0000.1700.3410.0280.0250.0000.1550.0990.1160.1320.0000.1250.1630.1450.1560.1180.1580.0940.1340.1820.1140.0930.0760.0090.0070.0000.0180.0320.0330.0230.0000.0000.0100.0790.0780.0510.1840.0260.0150.0930.0300.0640.0000.0470.0000.0160.0000.0000.2070.0000.1460.2160.0230.1240.1200.1190.0090.3330.7480.1500.2670.0190.0490.023
Generator RPM Min. [RPM]0.0000.0000.0000.0060.0190.0670.0700.0340.0810.0340.2250.0360.3580.2320.0150.0020.0000.0060.0290.0090.0650.0930.0630.0760.1070.0720.0190.0320.0350.0140.0070.0010.0060.3600.1701.0000.2740.0410.0260.0100.2470.1030.1090.1130.0000.1090.0710.1400.0890.1390.0610.1480.0820.3140.2010.2420.1960.0000.0050.0000.0150.0190.0220.0160.0250.0140.0260.0990.0520.2330.4140.0080.0000.1150.0000.0700.0240.0340.0000.0000.0000.0000.3640.1840.1500.3130.0260.2500.1340.2110.0720.3760.1570.7180.2240.0020.0130.057
Generator RPM StdDev [RPM]0.0140.0110.0000.0180.0320.0860.0700.0420.0480.0710.2220.0450.2450.3650.0140.0170.0040.0200.0210.0170.0670.0980.0730.0670.0950.0890.0560.0250.0250.0170.0380.0310.0310.4660.3410.2741.0000.0250.0130.0000.2620.1170.1370.1450.0000.1640.1710.2590.2100.1540.1470.1810.2170.2000.1280.1550.2210.0000.0040.0000.0230.0300.0270.0110.0080.0080.0140.1140.0810.0000.2180.0250.0110.1070.0150.0560.0080.1030.0000.0000.0000.0000.2850.0000.1370.2670.0100.2850.1510.1230.0830.4200.2870.2300.6920.0120.0650.083
Generator SlipRing Temp. Avg. [°C]0.0140.0050.0000.0270.0120.0150.0180.0130.0110.0000.0420.0320.0390.0220.0090.0130.0000.0000.0480.0280.0560.0510.0330.0570.0520.0580.0080.0230.0000.0310.0080.0070.0000.0570.0280.0410.0251.0000.0050.0000.0230.0000.0110.0080.0000.0180.0110.0010.0180.0200.0130.0000.0110.0290.0100.0290.0080.0040.0070.0050.0170.0300.0000.1070.0110.0080.0110.0000.0000.0120.0420.0000.0000.0060.0000.0060.0290.0000.0200.0820.0000.0000.0450.0290.0090.0400.0090.0200.0240.0340.0220.0480.0290.0410.0270.0180.0060.000
Grid Busbar Temp. Avg. [°C]0.0000.0000.0000.0080.0020.0000.0000.0000.0000.0030.0140.0100.0140.0110.0000.0080.0000.0140.0420.0000.0060.0190.0000.0130.0270.0080.0150.0070.0220.0000.0100.0000.0170.0060.0250.0260.0130.0051.0000.0000.0000.0000.0000.0000.0080.0030.0060.0160.0000.0070.0020.0140.0000.0060.0000.0090.0160.0030.0000.0000.0000.0000.0000.0000.0160.0360.0230.0190.0050.0220.0140.0000.0000.0240.0000.0180.0000.0040.0290.0330.0000.0000.0070.0250.0040.0090.0180.0120.0140.0210.0000.0000.0220.0110.0130.0000.0100.000
Grid InverterPhase1 Temp. Avg. [°C]0.0000.0050.0000.0080.0110.0160.0350.0190.0200.0060.0220.0000.0080.0110.0080.0090.0040.0310.0000.1580.0360.0350.0370.0410.0210.0000.0100.0000.0130.0910.0840.0730.0760.0000.0000.0100.0000.0000.0001.0000.0190.0620.0720.0860.0050.0430.0170.0130.0130.0540.0430.0250.0180.0210.0150.0150.0300.0090.0000.0000.2060.2100.2030.0080.0000.0000.0000.0100.0150.0000.0010.0000.0000.0140.0000.0000.0050.0000.0070.0000.0000.0000.0000.0260.0150.0270.0150.0000.0580.0000.0110.0000.0000.0000.0080.0070.0000.014
Grid Production CosPhi Avg.0.0000.0150.0000.0000.0250.0780.0320.0360.0260.0280.2460.1630.3320.2720.0000.0150.0120.0260.0110.0000.0310.0320.0000.0350.0550.0300.0440.0150.0180.0100.0260.0190.0230.1860.1550.2470.2620.0230.0000.0191.0000.1780.1800.2180.0000.1920.1880.2300.1850.2480.2210.1890.1960.4220.2750.2330.2700.0000.0000.0100.0150.0180.0190.0080.0000.0120.0000.1070.0930.0020.4420.0470.0170.1200.0410.0940.0640.0870.0060.0160.0000.0000.5960.0090.2040.5570.0560.3740.2400.2790.0710.2010.1370.1860.2170.0030.0600.062
Grid Production CurrentPhase1 Avg. [A]0.0000.0160.0000.0240.0000.0100.2130.0720.0560.0290.1530.0840.1110.0820.0000.0180.0100.0090.0000.0060.0630.0630.0630.0700.0410.0360.0370.0360.0310.0040.0460.0310.0380.1320.0990.1030.1170.0000.0000.0620.1781.0000.7330.7080.0020.5240.2540.2760.2420.6140.2920.3310.2600.1720.1070.1120.0950.0050.0120.0050.0590.0430.0410.0200.0040.0090.0030.0950.0880.0430.1350.0060.0080.1030.0000.0100.1140.0750.0000.0000.0000.0000.2270.1780.3300.2120.0050.0830.5910.1110.0040.1310.0790.0790.0980.0030.0510.000
Grid Production CurrentPhase2 Avg. [A]0.0000.0090.0000.0220.0110.0000.2030.0830.0550.0360.1640.0940.1210.0970.0020.0230.0000.0080.0000.0290.0700.0580.0550.0680.0270.0340.0410.0350.0140.0180.0550.0470.0430.1450.1160.1090.1370.0110.0000.0720.1800.7331.0000.7500.0070.5440.2710.2950.2590.6020.3180.3250.2760.1930.1250.1250.1150.0070.0110.0100.0670.0530.0610.0250.0000.0080.0060.0970.0870.0440.1550.0130.0080.1090.0000.0210.0960.0860.0000.0000.0000.0000.2170.1790.3580.2350.0050.0930.5880.1240.0050.1380.0920.0800.1110.0000.0590.000
Grid Production CurrentPhase3 Avg. [A]0.0000.0100.0000.0300.0130.0070.2190.0990.0630.0360.2000.1250.1430.1140.0000.0180.0000.0060.0000.0310.0680.0670.0630.0810.0390.0380.0390.0280.0240.0150.0520.0420.0430.1630.1320.1130.1450.0080.0000.0860.2180.7080.7501.0000.0000.5960.3110.3170.3000.6670.3540.3390.3100.2170.1410.1260.1270.0000.0000.0020.0660.0630.0620.0180.0060.0000.0000.0940.0860.0460.1920.0000.0090.1020.0000.0100.0800.0870.0000.0000.0000.0000.2790.1790.3910.2610.0060.1030.6570.1430.0040.1600.1060.0900.1210.0000.0660.000
Grid Production Frequency Avg. [Hz]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0040.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0080.0050.0000.0020.0070.0001.0000.0000.0020.0000.0050.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0040.0000.0000.0000.0000.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.000
Grid Production PossiblePower Avg. [W]0.0170.0120.0000.0240.0000.0160.2340.0850.0610.0290.2070.1360.1580.1520.0000.0090.0060.0000.0170.0110.0700.0490.0550.0700.0420.0330.0630.0280.0290.0000.0420.0400.0330.1510.1250.1090.1640.0180.0030.0430.1920.5240.5440.5960.0001.0000.3500.4090.3840.7320.3090.3290.3430.1530.1210.0770.1230.0000.0000.0000.0500.0370.0280.0220.0000.0030.0050.0570.0660.0370.2220.0160.0100.0570.0030.0120.0750.0780.0000.0070.0000.0000.2380.2850.4250.1780.0370.1380.7020.1180.0010.1430.1010.0840.1560.0000.0850.002
Grid Production PossiblePower Max. [W]0.0000.0200.0250.0090.0000.0040.0770.0990.0320.0260.1860.1500.1380.1390.0000.0160.0000.0140.0130.0000.0510.0300.0470.0400.0380.0500.0720.0060.0090.0000.0120.0120.0160.1700.1630.0710.1710.0110.0060.0170.1880.2540.2710.3110.0020.3501.0000.2860.3540.3200.6850.2110.2810.1520.1210.0600.1210.0090.0000.0000.0050.0080.0000.0170.0000.0000.0000.0660.0680.0170.1880.0000.0070.0690.0000.0000.0240.0680.0000.0000.0250.0250.2150.0530.2650.1790.0450.1320.3210.1420.0000.1520.1370.0570.1700.0130.0690.000
Grid Production PossiblePower Min. [W]0.0000.0000.0000.0200.0030.0000.0860.0450.0920.0300.2330.1200.1910.2650.0000.0110.0130.0000.0270.0000.0280.0290.0210.0420.0390.0300.0450.0180.0180.0000.0000.0000.0000.1420.1450.1400.2590.0010.0160.0130.2300.2760.2950.3170.0000.4090.2861.0000.3240.3630.2660.5940.3090.1650.1110.0800.1890.0000.0000.0000.0240.0130.0070.0000.0170.0200.0100.0500.0480.0470.2280.0000.0000.0510.0000.0000.0470.1110.0100.0000.0000.0000.2260.0950.3060.1940.0080.2800.3640.1190.0140.1340.1210.1060.2330.0110.0850.020
Grid Production PossiblePower StdDev [W]0.0290.0100.0000.0140.0070.0000.0410.0670.0350.1190.2300.1440.1940.2220.0000.0000.0000.0000.0200.0160.0260.0310.0360.0360.0330.0380.0340.0280.0180.0000.0260.0340.0320.1650.1560.0890.2100.0180.0000.0130.1850.2420.2590.3000.0050.3840.3540.3241.0000.3360.2980.2360.7390.2030.1630.0950.1350.0000.0000.0000.0080.0110.0020.0090.0080.0000.0260.0520.0560.0380.2360.0000.0000.0560.0000.0000.0430.0990.0050.0000.0000.0000.2360.0880.2880.2010.0490.1480.3410.1560.0000.1570.1340.0740.1940.0090.0690.005
Grid Production Power Avg. [W]0.0000.0100.0000.0250.0030.0120.2260.0810.0590.0310.2140.1310.1690.1320.0000.0100.0000.0000.0150.0160.0780.0590.0600.0770.0550.0360.0630.0280.0330.0000.0330.0410.0280.1600.1180.1390.1540.0200.0070.0540.2480.6140.6020.6670.0000.7320.3200.3630.3361.0000.3440.3640.3450.1840.1230.1070.1260.0000.0000.0000.0530.0450.0330.0290.0090.0000.0060.1080.0830.0530.2170.0000.0090.1180.0000.0280.0700.0910.0000.0000.0000.0000.3220.2970.4420.2280.0160.1350.8760.1400.0030.1580.0940.1100.1460.0110.0760.000
Grid Production Power Max. [W]0.0120.0040.0000.0170.0130.0000.0640.0910.0310.0310.1720.1300.1220.1110.0000.0270.0080.0180.0030.0090.0470.0360.0330.0450.0260.0360.0680.0000.0060.0000.0430.0400.0510.1510.1580.0610.1470.0130.0020.0430.2210.2920.3180.3540.0000.3090.6850.2660.2980.3441.0000.2140.2910.1690.1480.0680.1050.0090.0000.0030.0210.0300.0250.0200.0000.0090.0120.0560.0620.0030.1770.0150.0000.0700.0000.0340.0070.0490.0000.0110.0000.0000.2180.0410.2580.2090.0140.1070.3410.1370.0000.1390.1270.0470.1500.0130.0600.000
Grid Production Power Min. [W]0.0250.0000.0000.0200.0000.0090.0960.0500.0920.0240.1780.0740.1600.1880.0000.0250.0000.0040.0090.0000.0170.0240.0200.0260.0120.0190.0400.0340.0210.0000.0100.0020.0100.0950.0940.1480.1810.0000.0140.0250.1890.3310.3250.3390.0000.3290.2110.5940.2360.3640.2141.0000.2490.1410.0940.1170.1400.0000.0000.0000.0190.0080.0020.0110.0000.0150.0000.0450.0220.0500.1720.0000.0000.0460.0000.0000.0500.1120.0060.0050.0000.0000.1960.0890.2790.1450.0000.2100.3540.0930.0000.0990.0740.1130.1610.0000.0740.007
Grid Production Power StdDev [W]0.0120.0040.0000.0100.0150.0000.0370.0550.0470.1190.2200.1000.1970.2280.0110.0000.0000.0120.0060.0120.0210.0300.0280.0230.0230.0200.0330.0170.0210.0000.0470.0430.0450.1440.1340.0820.2170.0110.0000.0180.1960.2600.2760.3100.0000.3430.2810.3090.7390.3450.2910.2491.0000.2310.1600.1010.1660.0000.0000.0000.0170.0230.0150.0000.0150.0030.0260.1020.0970.0530.2170.0260.0030.1060.0220.0440.0250.0910.0120.0000.0000.0000.2460.0830.2690.2110.0670.1500.3480.1610.0080.1370.1060.0640.1960.0070.0520.000
Grid Production ReactivePower Avg. [W]0.0060.0300.0000.0080.0300.0950.0340.0360.0760.0310.3760.1520.6330.4800.0080.0290.0080.0000.0220.0040.0110.0320.0000.0300.0610.0210.0280.0270.0280.0090.0130.0000.0000.1990.1820.3140.2000.0290.0060.0210.4220.1720.1930.2170.0000.1530.1520.1650.2030.1840.1690.1410.2311.0000.5590.4190.4900.0050.0000.0000.0140.0150.0270.0210.0330.0230.0300.1580.1260.3430.6400.0590.0240.1600.0450.1000.0410.0600.0000.0000.0000.0000.5850.1720.2990.6720.2060.5510.1760.6550.0700.2110.1590.2390.1660.0130.0420.066
Grid Production ReactivePower Max. [W]0.0160.0180.0270.0170.0070.0510.0270.0340.0550.0240.2400.1160.4340.3290.0100.0080.0000.0000.0090.0000.0300.0240.0080.0300.0490.0240.0110.0120.0210.0020.0310.0310.0190.1180.1140.2010.1280.0100.0000.0150.2750.1070.1250.1410.0000.1210.1210.1110.1630.1230.1480.0940.1600.5591.0000.3510.3520.0000.0040.0000.0190.0130.0280.0110.0070.0000.0160.0950.0630.2310.4180.0250.0180.0810.0320.0460.0520.1320.0140.0000.0270.0270.3460.1210.2180.3560.2190.3390.1230.4410.0260.1270.1000.1640.0980.0000.0320.029
Grid Production ReactivePower Min. [W]0.0000.0270.0000.0000.0160.0700.0270.0290.0550.0240.2160.0620.3490.2710.0140.0000.0000.0050.0140.0070.0330.0410.0200.0370.0450.0370.0280.0120.0230.0070.0000.0180.0170.1530.0930.2420.1550.0290.0090.0150.2330.1120.1250.1260.0000.0770.0600.0800.0950.1070.0680.1170.1010.4190.3511.0000.2840.0090.0050.0160.0200.0210.0190.0150.0110.0170.0130.1030.0720.1490.3250.0430.0210.0940.0270.0570.0390.1960.0080.0110.0000.0000.3410.0750.1450.3400.0730.3050.1010.2930.0520.1560.0830.2110.1280.0060.0320.042
Grid Production ReactivePower StdDev [W]0.0000.0330.0000.0020.0120.0290.0200.0310.0560.0210.2210.0430.3920.3950.0040.0220.0030.0000.0140.0040.0170.0080.0000.0150.0300.0000.0470.0210.0270.0000.0000.0000.0000.0970.0760.1960.2210.0080.0160.0300.2700.0950.1150.1270.0040.1230.1210.1890.1350.1260.1050.1400.1660.4900.3520.2841.0000.0000.0000.0000.0160.0200.0200.0000.0230.0280.0150.0840.0650.2820.4280.0310.0130.0750.0220.0450.0160.0760.0070.0000.0000.0000.3170.1850.2140.3280.1850.4400.1270.3840.0400.0980.0670.1340.2100.0260.0350.069
Grid Production VoltagePhase1 Avg. [V]0.0000.0000.0000.0150.0060.0070.0000.0000.0000.0000.0000.0040.0000.0000.0150.0000.0150.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0080.0090.0000.0000.0040.0030.0090.0000.0050.0070.0000.0000.0000.0090.0000.0000.0000.0090.0000.0000.0050.0000.0090.0001.0000.5460.5480.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0090.0000.0090.0000.0080.0000.0100.0000.0030.0070.0000.0000.0110.0000.000
Grid Production VoltagePhase2 Avg. [V]0.0000.0080.0000.0090.0000.0120.0000.0000.0050.0000.0040.0110.0000.0000.0160.0000.0000.0000.0000.0000.0030.0000.0000.0000.0010.0000.0000.0040.0060.0130.0200.0000.0140.0000.0070.0050.0040.0070.0000.0000.0000.0120.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0050.0000.5461.0000.5000.0000.0040.0000.0000.0000.0050.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0060.0080.0000.0000.0000.0000.0000.0000.0060.0000.0110.0000.0000.0000.000
Grid Production VoltagePhase3 Avg. [V]0.0000.0000.0000.0150.0000.0000.0000.0110.0000.0000.0000.0090.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0070.0150.0120.0000.0190.0000.0000.0000.0000.0050.0000.0000.0100.0050.0100.0020.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0160.0000.5480.5001.0000.0050.0130.0020.0060.0000.0000.0000.0000.0000.0220.0000.0000.0000.0000.0000.0000.0000.0040.0000.0100.0000.0000.0100.0020.0160.0110.0000.0020.0000.0030.0000.0090.0000.0000.0000.0000.0030.000
Grid RotorInvPhase1 Temp. Avg. [°C]0.0000.0000.0000.0140.0090.0000.0290.0190.0200.0270.0070.0000.0170.0160.0040.0010.0000.0270.0100.1970.0560.0510.0230.0660.0320.0210.0100.0090.0000.1430.0530.0660.0660.0100.0180.0150.0230.0170.0000.2060.0150.0590.0670.0660.0000.0500.0050.0240.0080.0530.0210.0190.0170.0140.0190.0200.0160.0000.0000.0051.0000.3950.4070.0060.0000.0110.0060.0000.0000.0000.0000.0050.0000.0000.0000.0010.0090.0000.0000.0010.0000.0000.0020.0210.0200.0230.0230.0000.0470.0000.0050.0140.0080.0120.0170.0140.0000.000
Grid RotorInvPhase2 Temp. Avg. [°C]0.0000.0050.0000.0120.0000.0000.0250.0230.0240.0210.0210.0150.0240.0140.0000.0100.0000.0250.0000.2550.0550.0630.0310.0620.0420.0410.0200.0040.0000.1620.0670.0620.0590.0270.0320.0190.0300.0300.0000.2100.0180.0430.0530.0630.0000.0370.0080.0130.0110.0450.0300.0080.0230.0150.0130.0210.0200.0000.0040.0130.3951.0000.2990.0120.0000.0080.0060.0000.0000.0000.0100.0070.0000.0000.0000.0050.0220.0000.0030.0000.0000.0000.0150.0190.0200.0330.0250.0000.0420.0000.0000.0250.0300.0260.0290.0000.0000.000
Grid RotorInvPhase3 Temp. Avg. [°C]0.0140.0000.0000.0110.0060.0000.0350.0160.0200.0260.0300.0000.0230.0130.0000.0000.0000.0350.0000.2080.0650.0670.0300.0640.0540.0370.0140.0280.0000.1590.0670.0820.0690.0270.0330.0220.0270.0000.0000.2030.0190.0410.0610.0620.0000.0280.0000.0070.0020.0330.0250.0020.0150.0270.0280.0190.0200.0000.0000.0020.4070.2991.0000.0210.0070.0150.0140.0000.0080.0000.0120.0000.0000.0000.0000.0000.0140.0080.0000.0000.0000.0000.0190.0110.0140.0340.0260.0000.0360.0000.0000.0250.0340.0270.0130.0100.0000.000
HVTrafo AirOutlet Temp. Avg. [°C]0.0000.0000.0000.0090.0000.0200.0130.0090.0150.0010.0300.0130.0310.0160.0000.0000.0000.0060.0240.0050.0180.0230.0150.0230.0180.0170.0190.0110.0050.0200.0030.0000.0120.0270.0230.0160.0110.1070.0000.0080.0080.0200.0250.0180.0000.0220.0170.0000.0090.0290.0200.0110.0000.0210.0110.0150.0000.0000.0000.0060.0060.0120.0211.0000.0130.0160.0320.0000.0000.0230.0200.0000.0000.0040.0030.0000.0080.0130.0080.0600.0000.0000.0130.0440.0000.0100.0020.0060.0280.0140.0000.0270.0160.0180.0120.0100.0000.000
HVTrafo Phase1 Temp. Avg. [°C]0.0000.0000.0000.0000.0080.0050.0100.0000.0000.0000.0240.0000.0290.0350.0000.0000.0000.0000.0350.0110.0000.0240.0120.0000.0210.0070.0000.0400.0280.0240.0270.0250.0080.0050.0000.0250.0080.0110.0160.0000.0000.0040.0000.0060.0000.0000.0000.0170.0080.0090.0000.0000.0150.0330.0070.0110.0230.0000.0000.0000.0000.0000.0070.0131.0000.1770.2170.0000.0000.0570.0460.0000.0000.0000.0000.0000.0210.0080.0110.0190.0000.0000.0020.0590.0060.0000.0000.0340.0000.0180.0000.0000.0000.0200.0030.0000.0000.002
HVTrafo Phase2 Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0010.0070.0330.0300.0000.0000.0000.0120.0360.0130.0060.0090.0150.0130.0140.0000.0080.0310.0410.0180.0220.0280.0180.0000.0000.0140.0080.0080.0360.0000.0120.0090.0080.0000.0000.0030.0000.0200.0000.0000.0090.0150.0030.0230.0000.0170.0280.0080.0050.0000.0110.0080.0150.0160.1771.0000.1780.0000.0000.0490.0380.0000.0000.0000.0000.0040.0210.0070.0000.0240.0000.0000.0100.0420.0220.0000.0000.0440.0000.0090.0080.0000.0050.0210.0170.0100.0000.000
HVTrafo Phase3 Temp. Avg. [°C]0.0000.0000.0000.0120.0110.0000.0000.0000.0030.0000.0300.0000.0350.0350.0110.0050.0000.0210.0400.0140.0000.0190.0090.0000.0140.0140.0000.0540.0290.0380.0180.0250.0020.0130.0100.0260.0140.0110.0230.0000.0000.0030.0060.0000.0000.0050.0000.0100.0260.0060.0120.0000.0260.0300.0160.0130.0150.0000.0000.0000.0060.0060.0140.0320.2170.1781.0000.0000.0000.0400.0380.0000.0000.0000.0000.0020.0290.0170.0000.0210.0000.0000.0180.0490.0090.0120.0000.0400.0000.0130.0040.0010.0080.0250.0110.0000.0000.000
HourCounters Average AlarmActive Avg. [h]0.0000.2970.2060.0060.0120.0600.0000.0000.0150.0000.1450.0800.1260.1150.0550.0390.0000.0050.0140.0000.0040.0110.0300.0180.0070.0070.0640.0090.0000.0000.0050.0000.0110.0990.0790.0990.1140.0000.0190.0100.1070.0950.0970.0940.0000.0570.0660.0500.0520.1080.0560.0450.1020.1580.0950.1030.0840.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.6390.1660.0260.3570.3310.8700.3740.5210.0860.0180.0000.0110.2060.2060.2310.1190.0060.2060.0620.0340.1120.1130.0240.1030.0580.0790.0900.0090.0000.040
HourCounters Average AmbientOk Avg. [h]0.0000.3280.1420.0090.0060.0610.0000.0000.0410.0000.0990.0770.0780.0910.0480.0410.0000.0050.0000.0020.0070.0150.0210.0120.0000.0000.0430.0030.0000.0000.0080.0000.0060.0770.0780.0520.0810.0000.0050.0150.0930.0880.0870.0860.0000.0660.0680.0480.0560.0830.0620.0220.0970.1260.0630.0720.0650.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.6391.0000.1140.0130.6020.4250.6450.3310.3100.1240.0200.0000.0140.1420.1420.1590.0940.0000.1490.0510.0000.0870.0830.0550.0830.0590.0420.0580.0070.0000.033
HourCounters Average Gen1 Avg. [h]0.0000.0120.0000.0000.0150.0000.0150.0220.0630.0000.1400.0210.3140.2400.0000.0330.0120.0250.0170.0000.0000.0060.0000.0000.0180.0110.0190.0380.0140.0000.0280.0220.0270.0370.0510.2330.0000.0120.0220.0000.0020.0430.0440.0460.0050.0370.0170.0470.0380.0530.0030.0500.0530.3430.2310.1490.2820.0000.0010.0220.0000.0000.0000.0230.0570.0490.0400.1660.1141.0000.5750.0370.0000.1840.0380.1110.0070.0170.0000.0160.0000.0000.0270.5890.3660.0170.2580.2060.0530.2560.0070.0460.0330.1900.0080.0000.0000.008
HourCounters Average Gen2 Avg. [h]0.0190.0000.0000.0000.0300.0900.0410.0410.0550.0160.3610.1420.5380.4120.0000.0140.0030.0000.0240.0000.0230.0480.0090.0410.0830.0340.0250.0480.0360.0070.0000.0000.0000.2230.1840.4140.2180.0420.0140.0010.4420.1350.1550.1920.0040.2220.1880.2280.2360.2170.1770.1720.2170.6400.4180.3250.4280.0070.0000.0000.0000.0100.0120.0200.0460.0380.0380.0260.0130.5751.0000.0000.0000.0320.0000.0180.0310.0690.0070.0000.0000.0000.6270.3090.5100.5330.1090.5060.2180.4520.0820.2360.1630.3290.1780.0080.0440.074
HourCounters Average GridOk Avg. [h]0.0000.4770.2180.0060.0000.0170.0000.0000.0690.0000.0400.0340.0390.0530.0800.0250.0080.0000.0100.0000.0000.0010.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0170.0260.0080.0250.0000.0000.0000.0470.0060.0130.0000.0000.0160.0000.0000.0000.0000.0150.0000.0260.0590.0250.0430.0310.0000.0000.0000.0050.0070.0000.0000.0000.0000.0000.3570.6020.0370.0001.0000.6510.3400.5080.4770.0790.0000.0000.0150.2180.2180.0860.0000.0000.0720.0000.0000.0070.0380.0870.0180.0190.0000.0190.0100.0070.054
HourCounters Average GridOn Avg. [h]0.0000.7430.5010.0130.0000.0190.0000.0000.0830.0000.0130.0250.0070.0250.1280.0210.0220.0000.0070.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0150.0000.0110.0000.0000.0000.0170.0080.0080.0090.0000.0100.0070.0000.0000.0090.0000.0000.0030.0240.0180.0210.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.3310.4250.0000.0000.6511.0000.1760.3820.2760.1110.0000.0000.0140.5010.5010.0470.0000.0000.0340.0000.0030.0090.0110.0940.0000.0040.0000.0060.0010.0000.092
HourCounters Average Run Avg. [h]0.0000.1280.0150.0000.0110.0720.0000.0000.0090.0000.1610.0900.1440.1010.0340.0420.0040.0020.0220.0000.0100.0160.0360.0240.0130.0120.0740.0070.0000.0000.0000.0000.0090.1120.0930.1150.1070.0060.0240.0140.1200.1030.1090.1020.0000.0570.0690.0510.0560.1180.0700.0460.1060.1600.0810.0940.0750.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.8700.6450.1840.0320.3400.1761.0000.1990.6180.0730.0120.0000.0130.0150.0150.2260.1320.0000.2000.0650.0240.1220.1090.0000.1170.0720.0930.0820.0130.0000.000
HourCounters Average ServiceOn Avg. [h]0.0000.3120.2630.0000.0000.0000.0000.0000.0190.0000.0420.0260.0310.0400.0500.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0200.0300.0000.0150.0000.0000.0000.0410.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0220.0450.0320.0270.0220.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.3740.3310.0380.0000.5080.3820.1991.0000.3120.0470.0000.0000.0090.2630.2630.0680.0000.0000.0530.0000.0000.0010.0280.0050.0210.0190.0000.0110.0000.0110.046
HourCounters Average TurbineOk Avg. [h]0.0000.1770.0260.0030.0000.0440.0000.0000.0240.0000.0990.0650.1000.0540.0340.0300.0140.0000.0350.0000.0000.0050.0160.0030.0010.0000.0440.0020.0000.0000.0010.0000.0000.0520.0640.0700.0560.0060.0180.0000.0940.0100.0210.0100.0000.0120.0000.0000.0000.0280.0340.0000.0440.1000.0460.0570.0450.0000.0000.0000.0010.0050.0000.0000.0000.0040.0020.5210.3100.1110.0180.4770.2760.6180.3121.0000.0330.0000.0000.0170.0260.0260.1440.0450.0000.1380.0300.0000.0340.0680.0000.0550.0530.0580.0430.0030.0000.000
HourCounters Average WindOk Avg. [h]0.0000.0790.0380.0120.0050.0060.0360.0390.0570.0050.0380.1570.0440.0140.0120.0000.0080.0000.0000.0210.0250.0140.0110.0470.0310.0660.0350.0170.0000.0240.0120.0200.0110.0000.0000.0240.0080.0290.0000.0050.0640.1140.0960.0800.0000.0750.0240.0470.0430.0700.0070.0500.0250.0410.0520.0390.0160.0000.0020.0000.0090.0220.0140.0080.0210.0210.0290.0860.1240.0070.0310.0790.1110.0730.0470.0331.0000.0300.0170.0120.0380.0380.0930.0080.0490.0720.0510.0280.0700.0030.0230.0000.0000.0410.0180.0200.0000.000
HourCounters Average Yaw Avg. [h]0.0000.0000.0000.0000.0070.0090.0190.0060.0170.0330.0880.0300.0430.1170.0210.0000.0000.0180.0110.0000.0060.0000.0000.0000.0000.0080.0000.0110.0000.0090.0000.0060.0050.0250.0470.0340.1030.0000.0040.0000.0870.0750.0860.0870.0000.0780.0680.1110.0990.0910.0490.1120.0910.0600.1320.1960.0760.0000.0000.0040.0000.0000.0080.0130.0080.0070.0170.0180.0200.0170.0690.0000.0000.0120.0000.0000.0301.0000.0000.0000.0000.0000.0870.0230.0970.0830.0300.1070.0880.0240.0000.0300.0440.0420.0700.0070.0470.004
Hydraulic Oil Temp. Avg. [°C]0.0070.0000.0000.0000.0060.0000.0080.0000.0210.0080.0320.0110.0180.0270.0000.0130.0080.0250.0050.0000.0240.0140.0210.0160.0090.0200.0110.0190.0000.0000.0000.0010.0080.0000.0000.0000.0000.0200.0290.0070.0060.0000.0000.0000.0170.0000.0000.0100.0050.0000.0000.0060.0120.0000.0140.0080.0070.0000.0000.0000.0000.0030.0000.0080.0110.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0170.0001.0000.0250.0000.0000.0090.0200.0140.0040.0260.0000.0000.0200.0130.0000.0000.0000.0000.0000.0060.000
Nacelle Temp. Avg. [°C]0.0000.0170.0000.0410.0000.0000.0000.0000.0000.0070.0000.0100.0080.0020.0000.0000.0150.0180.0530.0000.0090.0000.0100.0200.0290.0080.0210.0140.0250.0000.0030.0030.0000.0030.0160.0000.0000.0820.0330.0000.0160.0000.0000.0000.0000.0070.0000.0000.0000.0000.0110.0050.0000.0000.0000.0110.0000.0000.0000.0100.0010.0000.0000.0600.0190.0240.0210.0110.0140.0160.0000.0150.0140.0130.0090.0170.0120.0000.0251.0000.0000.0000.0170.0270.0000.0150.0330.0120.0000.0140.0000.0000.0130.0020.0000.0070.0000.000
Power factor set point0.0000.4090.9370.0080.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0470.0250.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0250.0000.0000.0000.0000.0000.0000.0000.0270.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.2060.1420.0000.0000.2180.5010.0150.2630.0260.0380.0000.0000.0001.0000.9370.0000.0000.0000.0000.0000.0000.0000.0000.0470.0000.0000.0000.0000.0000.0000.079
Power factor set point source0.0000.4090.9370.0080.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0470.0250.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0250.0000.0000.0000.0000.0000.0000.0000.0270.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.2060.1420.0000.0000.2180.5010.0150.2630.0260.0380.0000.0000.0000.9371.0000.0000.0000.0000.0000.0000.0000.0000.0000.0470.0000.0000.0000.0000.0000.0000.079
Production LatestAverage Active Power Gen 0 Avg. [W]0.0240.0400.0000.0010.0230.1340.0440.0340.0280.0240.3620.2090.4410.3180.0150.0090.0140.0190.0180.0000.0440.0620.0340.0640.0950.0620.0720.0240.0310.0010.0260.0160.0140.2850.2070.3640.2850.0450.0070.0000.5960.2270.2170.2790.0000.2380.2150.2260.2360.3220.2180.1960.2460.5850.3460.3410.3170.0120.0000.0100.0020.0150.0190.0130.0020.0100.0180.2310.1590.0270.6270.0860.0470.2260.0680.1440.0930.0870.0090.0170.0000.0001.0000.0130.2190.7650.0330.4220.3500.4040.1050.2960.1900.2880.2380.0190.0570.086
Production LatestAverage Active Power Gen 1 Avg. [W]0.0000.0060.0000.0190.0000.0130.0890.0360.0580.0000.0600.0180.1710.1170.0080.0140.0090.0120.0230.0050.0570.0510.0270.0510.0380.0030.0230.0340.0140.0000.0080.0000.0090.0550.0000.1840.0000.0290.0250.0260.0090.1780.1790.1790.0000.2850.0530.0950.0880.2970.0410.0890.0830.1720.1210.0750.1850.0090.0060.0020.0210.0190.0110.0440.0590.0420.0490.1190.0940.5890.3090.0000.0000.1320.0000.0450.0080.0230.0200.0270.0000.0000.0131.0000.0060.0000.1910.0920.3680.1650.0070.0550.0140.1470.0240.0000.0000.007
Production LatestAverage Active Power Gen 2 Avg. [W]0.0270.0000.0000.0180.0160.0060.1240.0530.0550.0140.2640.1120.2890.2590.0070.0150.0060.0100.0170.0000.0000.0000.0160.0090.0100.0030.0080.0330.0220.0000.0120.0180.0100.0940.1460.1500.1370.0090.0040.0150.2040.3300.3580.3910.0000.4250.2650.3060.2880.4420.2580.2790.2690.2990.2180.1450.2140.0000.0080.0160.0200.0200.0140.0000.0060.0220.0090.0060.0000.3660.5100.0000.0000.0000.0000.0000.0490.0970.0140.0000.0000.0000.2190.0061.0000.1750.0700.3010.4550.1990.0000.1000.1160.1230.1050.0000.0930.006
Production LatestAverage Reactive Power Gen 0 Avg. [var]0.0110.0290.0000.0200.0360.1330.0410.0310.0190.0240.3150.2080.3940.2860.0160.0140.0150.0210.0130.0140.0400.0510.0290.0580.0840.0530.0740.0170.0280.0180.0330.0270.0270.2690.2160.3130.2670.0400.0090.0270.5570.2120.2350.2610.0000.1780.1790.1940.2010.2280.2090.1450.2110.6720.3560.3400.3280.0090.0000.0110.0230.0330.0340.0100.0000.0000.0120.2060.1490.0170.5330.0720.0340.2000.0530.1380.0720.0830.0040.0150.0000.0000.7650.0000.1751.0000.0400.3980.2200.5010.1080.2790.1910.2460.2230.0220.0590.101
Production LatestAverage Reactive Power Gen 1 Avg. [var]0.0000.0030.0000.0000.0070.0220.0000.0000.0200.0190.0870.0230.2010.1670.0000.0000.0100.0130.0120.0150.0060.0100.0000.0000.0130.0130.0250.0000.0070.0200.0410.0390.0420.0000.0230.0260.0100.0090.0180.0150.0560.0050.0050.0060.0000.0370.0450.0080.0490.0160.0140.0000.0670.2060.2190.0730.1850.0000.0000.0000.0230.0250.0260.0020.0000.0000.0000.0620.0510.2580.1090.0000.0000.0650.0000.0300.0510.0300.0260.0330.0000.0000.0330.1910.0700.0401.0000.0650.0190.7310.0180.0070.0160.0090.0140.0320.0120.017
Production LatestAverage Reactive Power Gen 2 Avg. [var]0.0170.0000.0000.0000.0220.0410.0140.0040.0550.0230.2350.0560.4570.4740.0080.0180.0000.0160.0280.0000.0000.0180.0160.0000.0160.0110.0190.0380.0270.0000.0000.0000.0090.1170.1240.2500.2850.0200.0120.0000.3740.0830.0930.1030.0000.1380.1320.2800.1480.1350.1070.2100.1500.5510.3390.3050.4400.0080.0000.0020.0000.0000.0000.0060.0340.0440.0400.0340.0000.2060.5060.0000.0030.0240.0000.0000.0280.1070.0000.0120.0000.0000.4220.0920.3010.3980.0651.0000.1330.4100.0980.1250.1090.1860.2360.0060.0430.121
Production LatestAverage Total Active Power Avg. [W]0.0000.0110.0000.0240.0000.0130.2230.0910.0630.0270.2170.1320.1720.1360.0000.0120.0000.0000.0220.0160.0760.0610.0640.0760.0470.0380.0630.0320.0240.0000.0370.0410.0290.1640.1200.1340.1510.0240.0140.0580.2400.5910.5880.6570.0000.7020.3210.3640.3410.8760.3410.3540.3480.1760.1230.1010.1270.0000.0000.0000.0470.0420.0360.0280.0000.0000.0000.1120.0870.0530.2180.0070.0090.1220.0010.0340.0700.0880.0000.0000.0000.0000.3500.3680.4550.2200.0190.1331.0000.1370.0030.1620.0970.1090.1470.0100.0810.000
Production LatestAverage Total Reactive Power Avg. [var]0.0000.0120.0000.0120.0100.0590.0250.0210.0520.0000.2710.1080.4510.3370.0000.0150.0000.0000.0260.0000.0290.0190.0100.0340.0590.0160.0570.0140.0270.0000.0130.0100.0160.1480.1190.2110.1230.0340.0210.0000.2790.1110.1240.1430.0000.1180.1420.1190.1560.1400.1370.0930.1610.6550.4410.2930.3840.0100.0000.0030.0000.0000.0000.0140.0180.0090.0130.1130.0830.2560.4520.0380.0110.1090.0280.0680.0030.0240.0200.0140.0000.0000.4040.1650.1990.5010.7310.4100.1371.0000.0430.1470.1090.1580.1230.0400.0250.045
Reactive power generator 0,Total accumulated [var]0.0000.0750.0470.0000.0000.0330.0000.0000.0060.0000.0420.0000.0550.0800.0080.0000.0060.0090.0000.0000.0000.0430.0000.0040.0180.0050.0050.0000.0000.0000.0000.0070.0100.0590.0090.0720.0830.0220.0000.0110.0710.0040.0050.0040.0000.0010.0000.0140.0000.0030.0000.0000.0080.0700.0260.0520.0400.0000.0000.0000.0050.0000.0000.0000.0000.0080.0040.0240.0550.0070.0820.0870.0940.0000.0050.0000.0230.0000.0130.0000.0470.0470.1050.0070.0000.1080.0180.0980.0030.0431.0000.0590.0080.0550.0730.0020.0000.285
Rotor RPM Avg. [RPM]0.0000.0120.0000.0130.0190.0830.1100.0460.0480.0400.2280.0680.2300.1600.0000.0060.0100.0060.0210.0170.1030.1400.1180.1200.1540.1380.0350.0360.0210.0280.0370.0370.0260.7080.3330.3760.4200.0480.0000.0000.2010.1310.1380.1600.0000.1430.1520.1340.1570.1580.1390.0990.1370.2110.1270.1560.0980.0030.0060.0090.0140.0250.0250.0270.0000.0000.0010.1030.0830.0460.2360.0180.0000.1170.0210.0550.0000.0300.0000.0000.0000.0000.2960.0550.1000.2790.0070.1250.1620.1470.0591.0000.3120.3450.3820.0200.0290.058
Rotor RPM Max. [RPM]0.0130.0000.0000.0220.0260.0800.0750.0500.0290.0270.1860.1940.1420.1260.0000.0110.0000.0000.0130.0150.0600.0840.0720.0730.0870.0880.0740.0240.0210.0110.0190.0210.0200.3690.7480.1570.2870.0290.0220.0000.1370.0790.0920.1060.0000.1010.1370.1210.1340.0940.1270.0740.1060.1590.1000.0830.0670.0070.0000.0000.0080.0300.0340.0160.0000.0050.0080.0580.0590.0330.1630.0190.0040.0720.0190.0530.0000.0440.0000.0130.0000.0000.1900.0140.1160.1910.0160.1090.0970.1090.0080.3121.0000.1480.2250.0230.0390.026
Rotor RPM Min. [RPM]0.0000.0000.0000.0000.0120.0610.0640.0310.0720.0200.1800.0510.2950.1750.0190.0000.0060.0080.0240.0240.0660.1050.0660.0900.1120.0860.0000.0270.0340.0320.0000.0080.0150.3360.1500.7180.2300.0410.0110.0000.1860.0790.0800.0900.0000.0840.0570.1060.0740.1100.0470.1130.0640.2390.1640.2110.1340.0000.0110.0000.0120.0260.0270.0180.0200.0210.0250.0790.0420.1900.3290.0000.0000.0930.0000.0580.0410.0420.0000.0020.0000.0000.2880.1470.1230.2460.0090.1860.1090.1580.0550.3450.1481.0000.1910.0000.0060.045
Rotor RPM StdDev [RPM]0.0110.0130.0000.0120.0190.0670.0510.0350.0340.0520.1830.0460.2010.3020.0060.0110.0000.0230.0240.0070.0670.0940.0480.0680.0780.0720.0820.0220.0280.0080.0200.0120.0160.4020.2670.2240.6920.0270.0130.0080.2170.0980.1110.1210.0000.1560.1700.2330.1940.1460.1500.1610.1960.1660.0980.1280.2100.0000.0000.0000.0170.0290.0130.0120.0030.0170.0110.0900.0580.0080.1780.0190.0060.0820.0110.0430.0180.0700.0000.0000.0000.0000.2380.0240.1050.2230.0140.2360.1470.1230.0730.3820.2250.1911.0000.0280.0530.070
Spinner Temp. Avg. [°C]0.0120.0000.0000.0210.0000.0060.0070.0240.0000.0000.0150.0060.0000.0000.0110.0820.0160.0000.0070.0000.0310.0140.0140.0390.0340.0120.0400.0000.0000.0170.0130.0060.0120.0270.0190.0020.0120.0180.0000.0070.0030.0030.0000.0000.0040.0000.0130.0110.0090.0110.0130.0000.0070.0130.0000.0060.0260.0110.0000.0000.0140.0000.0100.0100.0000.0100.0000.0090.0070.0000.0080.0100.0010.0130.0000.0030.0200.0070.0000.0070.0000.0000.0190.0000.0000.0220.0320.0060.0100.0400.0020.0200.0230.0000.0281.0000.0090.000
Total Active power [W]0.0000.0000.0000.0000.0000.0070.0000.0000.0040.0000.0360.0580.0350.0590.0000.0080.0000.0030.0000.0000.0080.0030.0000.0000.0000.0000.0290.0000.0120.0000.0030.0000.0000.0300.0490.0130.0650.0060.0100.0000.0600.0510.0590.0660.0000.0850.0690.0850.0690.0760.0600.0740.0520.0420.0320.0320.0350.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0440.0070.0000.0000.0110.0000.0000.0470.0060.0000.0000.0000.0570.0000.0930.0590.0120.0430.0810.0250.0000.0290.0390.0060.0530.0091.0000.000
Total reactive power [var]0.0000.0740.0790.0000.0160.0000.0000.0000.0060.0000.0590.0000.0480.0890.0140.0000.0000.0090.0030.0130.0090.0170.0040.0110.0000.0100.0060.0000.0000.0000.0050.0070.0100.0520.0230.0570.0830.0000.0000.0140.0620.0000.0000.0000.0000.0020.0000.0200.0050.0000.0000.0070.0000.0660.0290.0420.0690.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0400.0330.0080.0740.0540.0920.0000.0460.0000.0000.0040.0000.0000.0790.0790.0860.0070.0060.1010.0170.1210.0000.0450.2850.0580.0260.0450.0700.0000.0001.000

Missing values

2025-05-15T14:25:29.687546image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-15T14:25:30.415440image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
02020-01-01 00:00:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
12020-01-01 00:10:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
22020-01-01 00:20:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
32020-01-01 00:30:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
42020-01-01 00:40:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
52020-01-01 00:50:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
62020-01-01 01:00:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
72020-01-01 01:10:0000000001000000000000000100000000000001000000000000000000000000000000000000000000000010000000000000000000000000000000000000000000
82020-01-01 01:20:0001100000000000000000000100000000000100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
92020-01-01 01:30:0000000000101000000000100100000000000001000000000000000010000000000000000000000010000000001000000010000000000000000000000000000000
TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
261982020-06-30 22:20:0000000000000000000000000000000000000100000000000000000000000000000000000000001000000010000000000000000000000000000000000000000000
261992020-06-30 22:30:0000000000000000000000000000000000000101000000000000000000000000000000000000000100000000000000000000000000000000000000000000000000
262002020-06-30 22:40:0000000000000000000000001000000000000001000000000000000000000000000000000000000010000000000000000000000000000000000000000000000000
262012020-06-30 22:50:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
262022020-06-30 23:00:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
262032020-06-30 23:10:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
262042020-06-30 23:20:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
262052020-06-30 23:30:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
262062020-06-30 23:40:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
262072020-06-30 23:50:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000